Sync July 30 catalog update

README.de.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>Datensätze, Benchmarks, Modelle und Werkzeuge für egozentrisches Sehen, verkörperte KI und Robotik, Video-Sprache, Langzeitgedächtnis, AR/VR und Hand-Objekt-Interaktion.</strong></p>
 
-<p align="center"><strong>793</strong> egozentrische Ressourcen — 202 Datensätze · 134 Benchmarks · 412 Modelle · 40 Toolkits</p>
+<p align="center"><strong>808</strong> egozentrische Ressourcen — 208 Datensätze · 137 Benchmarks · 415 Modelle · 42 Toolkits</p>
 
 ## Inhalt
 

README.es.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>Conjuntos de datos, benchmarks, modelos y herramientas para visión egocéntrica, IA encarnada y robótica, video-lenguaje, memoria de largo contexto, RA/RV e interacción mano-objeto.</strong></p>
 
-<p align="center"><strong>793</strong> recursos egocéntricos — 202 conjuntos de datos · 134 benchmarks · 412 modelos · 40 herramientas</p>
+<p align="center"><strong>808</strong> recursos egocéntricos — 208 conjuntos de datos · 137 benchmarks · 415 modelos · 42 herramientas</p>
 
 ## Qué incluye
 

README.fr.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>Jeux de données, benchmarks, modèles et outils pour la vision égocentrique, l'IA incarnée et la robotique, le vidéo-langage, la mémoire à long contexte, la RA/RV et l'interaction main-objet.</strong></p>
 
-<p align="center"><strong>793</strong> ressources égocentriques — 202 jeux de données · 134 benchmarks · 412 modèles · 40 outils</p>
+<p align="center"><strong>808</strong> ressources égocentriques — 208 jeux de données · 137 benchmarks · 415 modèles · 42 outils</p>
 
 ## Contenu
 

README.ja.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>エゴセントリック視覚、身体性 AI とロボティクス、ビデオ言語、長文脈記憶、AR/VR、手と物体の相互作用に使うデータセット・ベンチマーク・モデル・ツール。</strong></p>
 
-<p align="center"><strong>793</strong> エゴセントリック資源 — 202 データセット · 134 ベンチマーク · 412 モデル · 40 ツールキット</p>
+<p align="center"><strong>808</strong> エゴセントリック資源 — 208 データセット · 137 ベンチマーク · 415 モデル · 42 ツールキット</p>
 
 ## 収録内容
 

README.ko.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>자기중심 비전, 체화 AI와 로보틱스, 비디오-언어, 장문맥 기억, AR/VR, 손-물체 상호작용을 위한 데이터셋·벤치마크·모델·도구.</strong></p>
 
-<p align="center"><strong>793</strong> 자기중심 자원 — 202 데이터셋 · 134 벤치마크 · 412 모델 · 40 툴킷</p>
+<p align="center"><strong>808</strong> 자기중심 자원 — 208 데이터셋 · 137 벤치마크 · 415 모델 · 42 툴킷</p>
 
 ## 구성
 

README.md

@@ -103,7 +103,7 @@ The paper-focused sheet is also mirrored as [`awesome-egocentric-papers.csv`](aw
   <a href="https://github.com/ChaoYue0307/awesome-egocentric-atlas/actions/workflows/validate.yml"><img alt="validate" src="https://github.com/ChaoYue0307/awesome-egocentric-atlas/actions/workflows/validate.yml/badge.svg"></a>
   <a href="https://chaoyue0307.github.io/awesome-egocentric-atlas/"><img alt="project site" src="https://img.shields.io/badge/site-GitHub%20Pages-067882"></a>
   <a href="https://huggingface.co/datasets/cy0307/awesome-egocentric-atlas"><img alt="Hugging Face mirror" src="https://img.shields.io/badge/Hugging%20Face-mirror-ffcc4d"></a>
-  <a href="data/resources.yml"><img alt="resources" src="https://img.shields.io/badge/resources-793-0097A7"></a>
+  <a href="data/resources.yml"><img alt="resources" src="https://img.shields.io/badge/resources-808-0097A7"></a>
   <a href="README.md#dataset-atlas"><img alt="datasets" src="https://img.shields.io/badge/datasets-vision%20%7C%20robotics%20%7C%20memory-344054"></a>
   <a href="README.md#models-tools-and-baselines"><img alt="models and tools" src="https://img.shields.io/badge/models-and%20tools-F5A623"></a>
   <a href="LICENSE"><img alt="license" src="https://img.shields.io/badge/license-MIT-667085"></a>
@@ -112,7 +112,7 @@ The paper-focused sheet is also mirrored as [`awesome-egocentric-papers.csv`](aw
 
 **Awesome Egocentric Atlas** is a practical catalog of egocentric (first-person) datasets, benchmarks, models, and tools for egocentric vision, embodied AI and robotics, vision-language-action, world models, long-context memory, AR/VR, and hand-object interaction. Every entry shows its public-access status, so you can tell at a glance what you can download today and what is still just a paper.
 
-**Updated:** 2026-07-20.
+**Updated:** 2026-07-30.
 **Scope:** the main atlas is **human or animal first-person capture** from head, glasses, headset, body, wrist, handheld, or synchronized ego-exo rigs (where the ego view is central). Related but non-egocentric resources — robot-only datasets, multi-view robotic benchmarks, autonomous-driving 4D data, and general long-video reasoning — are listed separately under [Adjacent and Related Resources](#adjacent-and-related-resources) rather than in the main tables.
 
 <p align="center">
@@ -155,7 +155,7 @@ Prefer a browsable view? The [interactive site](https://chaoyue0307.github.io/aw
 
 | Signal | What it means for readers |
 | :--- | :--- |
-| 793 egocentric resources | 202 datasets, 134 benchmarks, 412 models, and 40 toolkits, plus 2 collection hubs — across vision, robotics, memory, and AR. 147 related non-egocentric resources are listed separately. |
+| 808 egocentric resources | 208 datasets, 137 benchmarks, 415 models, and 42 toolkits, plus 3 collection hubs — across vision, robotics, memory, and AR. 150 related non-egocentric resources are listed separately. |
 | 6 research areas | Foundation video, procedure/action, hands and 3D, memory/reasoning, robotics/VLA, and AR/wearable sensing. |
 | 5 access states | `open`, `request`, `benchmark`, `partial`, and `watch` keep availability visible before you plan experiments. |
 | Machine-checked catalog | [`data/resources.yml`](data/resources.yml) is the source for type, year, status, URL, tasks, and provenance — and CI keeps the public artifacts in sync. |
@@ -303,6 +303,11 @@ Egocentric human-manipulation and wrist-camera data aimed at vision-language-act
 
 | Resource | Released | Venue | Scale / signal | Best for | Status |
 | :--- | :---: | :---: | :--- | :--- | :---: |
+| [HiFi-UMI-2K](https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K) | 2026-07 | arXiv | 2,000 open hours from a high-fidelity UMI rig with head stereo-inertial SLAM, native inter-gripper pose, microsecond synchronization, and two ultra-wide cameras per hand | Robot-free VLA/WAM pretraining and direct manipulation-policy deployment | open |
+| [EgoRecovery](https://arxiv.org/abs/2607.19745) | 2026-07 | arXiv | Egocentric human recovery demonstrations collected at more than 10x robot-teleoperation throughput and aligned with a shared corrective-intent space | Learning when and how robots should recover from manipulation failures | watch |
+| [DDD Egocentric Stereo Manipulation Sample](https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset) | 2026-07 | Hugging Face | Ten open LeRobot v2 episodes (about 2.37 GB) with stereo first-person video and high-frequency hand/head pose | Stereo human-demonstration loaders, hand tracking, and sensor fusion | open |
+| [Showway Egocentric Origami Series](https://huggingface.co/datasets/showway-ego/egocentric-origami-001) | 2026-07 | Hugging Face | Nine open neck-mounted iPhone origami episodes across three LeRobot v3 repositories, with 3D hand joints and reviewed narration | Compact procedural HOI and imitation-learning experiments | open |
+| [EGXO Household Egocentric Video Evaluation](https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation) | 2026-07 | Hugging Face | 71 household-task videos totaling 10 hours; six previews are public and the complete 43.4 GiB media package is licensed by request | Household procedure and hand-object video evaluation | request |
 | [Let the Body Follow](https://arxiv.org/abs/2607.16095) | 2026-07 | arXiv | Coupled egocentric TIAGo teleoperation maps head and arm motion to coordinated torso and mobile-base control, reducing explicit controls and user workload | Whole-body mobile-manipulator teleoperation and HRI | watch |
 | [EgoHTR](https://egohtr.github.io/) | 2026-07 | arXiv | 55 scene-aligned 4D human-terrain sequences across seven environments, totaling 1.37 hours and about 150K frames from eight participants, with multiview and mocap ground truth | Scene-aware human-motion reconstruction and humanoid terrain traversal | watch |
 | [Open-AoE](https://huggingface.co/datasets/inclusionAI/OpenAoE-2000h) | 2026-07 | Hugging Face | Public nano and tiny tiers provide 2,821 smartphone first-person clips and about 103 hours with video, metric SLAM trajectories, MANO hands, and atomic actions; 2,000 hours remains a roadmap | Large-scale hand-motion, camera-trajectory, and manipulation pretraining | partial |
@@ -383,6 +388,7 @@ Egocentric human-manipulation and wrist-camera data aimed at vision-language-act
 | [HoMMI](https://hommi-robot.github.io/) | 2026-03 | arXiv | Whole-body mobile manipulation interface augmenting UMI with egocentric sensing, relaxed head actions, and cross-embodiment hand-eye policy design | Robot-free mobile manipulation demonstrations | watch |
 | [Ego-Exo Manufacturing](https://huggingface.co/datasets/third-origin/ego-exo-manufacturing) | 2026-03 | Hugging Face | Gated 275-hour shoe-manufacturing corpus with 40 synchronized ego-exo groups, 80 standalone ego sessions, 137 exo sessions, and procedure/proficiency/mistake annotations | Industrial ego-exo learning, skill assessment, and procedural modeling | request |
 | [OBayData Egocentric Dexterous Manipulation Demo](https://huggingface.co/datasets/obaydata/egocentric-dexterous-manipulation-demo) | 2026-03 | Hugging Face | 500 train and 100 test first-person manipulation sessions with head and wrist videos, 3D hand joints, camera extrinsics, action labels, and language annotations | Quality review and prototyping for dexterous human-demonstration pipelines | open |
+| [HuMI](https://humanoid-manipulation-interface.github.io/) | 2026-02 | arXiv | Portable robot-free whole-body demonstration interface with open code and seven Hugging Face datasets across kneeling, squatting, tossing, walking, and bimanual tasks | Humanoid whole-body manipulation from portable human demonstrations | open |
 | [Seesaw Video Subset](https://huggingface.co/datasets/SeesawVideos/Video_Subset) | 2026-02 | Hugging Face | 763 gated LeRobot-compatible indoor episodes, including 243 ego and 520 exo views, 321,178 frames, four room settings, and smartphone AR camera pose | Ego-exo robot learning, action recognition, and data-conversion experiments | request |
 | [CoMe-VLA](https://arxiv.org/abs/2602.04600) | 2026-02 | arXiv | Cognitive and memory-aware VLA that learns active-perception strategies from large-scale egocentric human data | Non-Markovian active perception and manipulation | watch |
 | [EgoAVFlow](https://arxiv.org/abs/2602.22461) | 2026-02 | arXiv | Learns manipulation and active camera control from egocentric human videos through shared 3D flow | Active-vision robot policy transfer | watch |
@@ -436,6 +442,8 @@ Fine-grained hand, object, contact, and 3D-pose datasets, including emerging eve
 
 | Resource | Released | Venue | Scale / signal | Best for | Status |
 | :--- | :---: | :---: | :--- | :--- | :---: |
+| [ReViV](https://reviv4d.github.io/) | 2026-07 | ECCV 2026 | Open unified feed-forward reconstruction of camera trajectory, gaze, body, hands, depth, and view dynamics from one monocular egocentric RGB stream | Holistic and efficient viewer-plus-scene 4D reconstruction | open |
+| [Egocentric Hand Benchmark Annotations](https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark) | 2026-07 | Hugging Face | 100,427 public annotation rows combining 95,002 EgoDaily hand boxes and 5,425 HOT3D virtual hand-crop camera records; source RGB is not redistributed | Hand detection, crop-camera geometry, and derived benchmark evaluation | partial |
 | [EgoExoMoCap](https://arxiv.org/abs/2607.15868) | 2026-07 | ECCV 2026 | Distributed mocap from two or more smart-glasses wearers, fusing head/wrist tracking with context-aware image features on two in-the-wild datasets | Lightweight ego-exo body-motion reconstruction | watch |
 | [Exo2EgoPose](https://arxiv.org/abs/2607.15890) | 2026-07 | ACM MM 2026 | Vision-language-guided egocentric 3D hand-pose forecasting using reconstructed exocentric demonstrations, evaluated on AssemblyHands, Ego-Exo4D, EgoMe-pose, and CALVIN | Hand forecasting and human-to-robot transfer | watch |
 | [EgoObjects-Camera](https://huggingface.co/datasets/KangLiao/EgoObjects-Camera) | 2026-07 | Hugging Face | Public camera-parameter annotations for 241,554 EgoObjects images across 49 shards, including roll, pitch, vertical field of view, and radial distortion; reuse terms are undeclared | Camera-aware egocentric modeling and dataset analysis | partial |
@@ -491,7 +499,7 @@ Fine-grained hand, object, contact, and 3D-pose datasets, including emerging eve
 | [EvHand-FPV](https://arxiv.org/abs/2509.13883) | 2025-09 | arXiv | Event-based first-person 3D hand-tracking dataset and lightweight wrist-ROI tracking framework | Low-power FPV hand tracking | watch |
 | [THOR](https://arxiv.org/abs/2507.06442) | 2025-07 | arXiv | Thermal-guided adaptive RGB sampling for wearable hand-object monitoring, using about 3% of RGB frames while preserving activity segments | Low-power longitudinal hand-object activity recognition | watch |
 | [Egocentric HOI Detection](https://arxiv.org/abs/2506.14189) | 2025-06 | Expert Systems with Applications | New benchmark and method for detecting hand-object interactions in egocentric video | Egocentric hand-object interaction detection | open |
-| [EgoBrain](https://arxiv.org/abs/2506.01353) | 2025-06 | arXiv | Synchronized EEG and egocentric video for human action understanding | Brain-signal plus first-person action understanding | watch |
+| [EgoBrain](https://huggingface.co/datasets/ut-vision/EgoBrain) | 2025-06 | ICLR 2026 | Complete gated 1.6 TB release from 40 participants with synchronized 4K egocentric video, EEG, IMU, interval markers, and surveys | Brain-signal plus first-person action understanding | request |
 | [EventEgoHands](https://arxiv.org/abs/2505.19169) | 2025-05 | ICIP 2025 | Event-based egocentric 3D hand mesh reconstruction benchmark over N-HOT3D | Low-light and motion-blur hand reconstruction | watch |
 | [EgoEvGesture](https://arxiv.org/abs/2503.12419) | 2025-03 | arXiv | First large-scale egocentric event-camera gesture-recognition dataset with a head-motion-robust 7M-param model (62.7% unseen-subject accuracy) | Event-camera egocentric gesture recognition | watch |
 | [EgoCast](https://arxiv.org/abs/2412.02903) | 2024-12 | WACV 2025 | 3D pose forecasting from egocentric video and proprioceptive data on Ego-Exo4D / Aria Digital Twin | Future body-pose forecasting | watch |
@@ -533,6 +541,7 @@ Long-horizon daily-life capture and the question-answering benchmarks that probe
 
 | Resource | Released | Venue | Scale / signal | Best for | Status |
 | :--- | :---: | :---: | :--- | :--- | :---: |
+| [Sidewalk Moments](https://arxiv.org/abs/2607.20903) | 2026-07 | arXiv | 61 first-person city walks segmented into more than 50K ten-second clips with video, averaged-image, audio, and text representations | Human-aligned urban engagement and multimodal temporal-compression studies | watch |
 | [Vinci2 / EgoServe](https://sitonggong.github.io/EgoServe-page/) | 2026-07 | ECCV 2026 | 3,000+ proactive-service instances across 11 categories and four memory horizons, with public annotations and the training-free EgoMemo agent | Deciding when an egocentric assistant should intervene and grounding its response in memory | open |
 | [VEGAS](https://arxiv.org/abs/2607.08489) | 2026-07 | arXiv | Training-free gaze-aware caption metric plus egocentric activities and instructional slides paired with synchronized gaze and reference captions | Human-attention-aligned caption evaluation and retrieval | watch |
 | [CoMind](https://comind.ethz.ch/) | 2026-07 | ECCV 2026 | Dual-view collaborative-cooking dataset with two synchronized head-mounted cameras, two exo views, audio, gaze, 3D scene/object scans, and social/interaction annotations; download is marked coming soon | Social reasoning, joint attention, handover prediction, and collaborative assistance | watch |
@@ -553,7 +562,7 @@ Long-horizon daily-life capture and the question-answering benchmarks that probe
 | [SuperMemory-VQA](https://arxiv.org/abs/2606.00825) | 2026-06 | arXiv | 52.9 hours of AI-glasses activity with RGB, audio, gaze, IMU, SLAM, and 4,853 human-verified QA pairs across object/location/intent/scene memory | Long-horizon memory for AR assistants | watch |
 | [EgoMonth](https://huggingface.co/datasets/anonymous-egomonth/egomonth-dataset) | 2026-05 | Hugging Face | 1,443 long-horizon memory QA records with event/object/place annotations and eight public sample videos; the full 20-120-day corpus uses external research access | Month-scale episodic memory, spatial reasoning, and personal QA | partial |
 | [VISTA Daily Assistance](https://arxiv.org/abs/2605.10579) | 2026-05 | arXiv | Generative egocentric-video framework for reactive and proactive daily-assistance scenarios | Synthetic training/evaluation for assistants | watch |
-| [EgoMemReason](https://arxiv.org/abs/2605.09874) | 2026-05 | arXiv | 500 questions over week-long egocentric video with entity, event, and behavior memory types | Memory-driven reasoning across sparse evidence over hours or days | watch |
+| [EgoMemReason](https://huggingface.co/datasets/Ted412/EgoMemReason) | 2026-05 | COLM 2026 | 500 public questions over week-long EgoLife video with entity, event, and behavior memory, open evaluation code, and a leaderboard | Memory-driven reasoning across sparse evidence over hours or days | open |
 | [EgoBench](https://arxiv.org/abs/2605.27820) | 2026-05 | arXiv | 1,045 egocentric-video-grounded interactive tasks with tools and simulated users | Tool-using multimodal agents with dynamic interaction | watch |
 | [EyeCue](https://github.com/langzhang2000/EyeCue) | 2026-05 | arXiv | Gaze-empowered egocentric video model plus CogDrive annotations for driver cognitive-distraction detection | Gaze-context reasoning for safety and internal-state inference | watch |
 | [Minerva-Ego](https://github.com/google-deepmind/neptune) | 2026-05 | arXiv | Complex egocentric visual-reasoning benchmark with multi-step multimodal questions, dense reasoning traces, and spatiotemporal object masks | Grounded multi-step egocentric reasoning | open |
@@ -568,6 +577,7 @@ Long-horizon daily-life capture and the question-answering benchmarks that probe
 | [EgoExoMem](https://arxiv.org/abs/2605.18734) | 2026-05 | arXiv | 2.6K MCQs across synchronized ego-exo videos | Cross-view memory reasoning | watch |
 | [EgoCoT-Bench](https://dstardust.github.io/EgoCoT/) | 2026-05 | arXiv | 3,172 verifiable QA pairs over 351 videos with operation-centric rationale annotations | Grounded chain-of-thought and evidence consistency | open |
 | [EgoStream](https://arxiv.org/abs/2605.31557) | 2026-05 | arXiv | 2,250 questions across seven memory dimensions with Answer Validity Windows, expanded to 8,528 recall-conditioned evaluations over streams up to 45.3 hours | Diagnosing streaming episodic memory | watch |
+| [ChildLens](https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/) | 2026-04 | Behavior Research Methods 2026 | 109 hours of vest-mounted first-person video/audio from 62 children aged 3-5 at home, with five location and 14 activity classes | Naturalistic child activity, temporal localization, and voice analysis | request |
 | [MyEgo](https://github.com/Ryougetsu3606/MyEgo) | 2026-04 | CVPR 2026 | 541 long videos and 5K personalized questions about the camera wearer, belongings, activities, and past | Personalized ego-grounding and long-range memory QA | open |
 | [EgoEsportsQA](https://arxiv.org/abs/2604.12320) | 2026-04 | arXiv | 1,745 QA pairs from professional first-person shooter matches across three games | High-speed first-person perception and tactical reasoning in virtual environments | watch |
 | [EgoEverything](https://arxiv.org/abs/2604.08342) | 2026-04 | arXiv | 5,000+ MCQ pairs over 100+ hours, with gaze-attention-inspired question generation for AR | Human-behavior-inspired long-context egocentric understanding | watch |
@@ -695,6 +705,8 @@ AR-glasses and headset data with gaze, SLAM, and digital-twin annotations for sc
 
 | Resource | Released | Venue | Scale / signal | Best for | Status |
 | :--- | :---: | :---: | :--- | :--- | :---: |
+| [CRAFT Wearable Creative AI](https://arxiv.org/abs/2607.21394) | 2026-07 | arXiv | Smart-glasses creative-AI probe informed by nine interviews, co-design with 16 participants, and 24 real-world sessions with eight writers | Context-aware wearable creativity and in-situ human-AI collaboration | watch |
+| [SHARE User-Centric AR SLAM](https://arxiv.org/abs/2607.23901) | 2026-07 | arXiv | User-prioritized edge SLAM for commercial AR headsets and a ground robot, reporting 13.22 ms AR latency and sub-2-centimeter tracking | Responsive AR interfaces in shared human-robot workspaces | watch |
 | [Ego6D Nymeria Features](https://huggingface.co/datasets/po03087/ego6d_rag) | 2026-07 | Hugging Face | Public Nymeria-derived 3D scene voxels, 20 Hz head 6-DoF windows over 149 scenes, and world-frame SMPL body pose over 148 scenes; terms are research-only and incomplete | Joint 3D scene, localization, and body-pose experiments | partial |
 | [HeadRoom](https://arxiv.org/abs/2607.08083) | 2026-07 | arXiv | Edge smart-glasses pipeline estimates visual and auditory channel availability from egocentric video/audio; a 25-participant study tests adaptive notification routing | Perceptual-load-aware wearable assistance | watch |
 | [Future-Privileged Causal Ego Gaze](https://arxiv.org/abs/2607.01437) | 2026-07 | arXiv | Causal egocentric gaze-estimation study showing future-aware training improves online models on EGTEA Gaze+ and Ego4D | Real-time gaze modeling for AR/wearables | watch |
@@ -734,6 +746,8 @@ Evaluation suites and label sets built on top of the raw datasets above.
 
 | Benchmark | Released | Venue | Built on | Tasks | Status |
 | :--- | :---: | :---: | :--- | :--- | :---: |
+| [HumanCLAW-Bench](https://human-claw.github.io/) | 2026-07 | arXiv | 1,218 egocentric find-navigate-interact episodes across 41 indoor scenes | VLM embodied decision-making, navigation, interaction, and body self-awareness | watch |
+| [EgoSafe-Bench](https://arxiv.org/abs/2607.26518) | 2026-07 | arXiv | 3,000 first-person mobile clips paired with hierarchical QA chains | 12,000 evaluations of evidence anchoring, blind spots, intent, causality, and safety reasoning | watch |
 | [VIABench](https://github.com/MCG-NJU/VIABench) | 2026-07 | arXiv | First-person videos recorded or shared by blind and visually impaired people | Proactive navigation reminders, assistive VideoQA, and vision-guided interaction in streaming and offline settings | watch |
 | [EgoProceVQA](https://z1oong.github.io/EgoProceVQA/) | 2026-07 | arXiv | 1,272 clips from CaptainCook4D, EPIC-Tent, Assembly101, and EgoOops | 3,600 QA pairs over 31 procedures and six key-step question types, plus EgoProceGen and EgoProceAgent | watch |
 | [EgoPolice](https://arxiv.org/abs/2607.06468) | 2026-07 | arXiv | Public police body-worn camera footage | Second-by-second high-stakes action labels, action classification, and multiple-choice QA over egocentric police-civilian interactions | watch |
@@ -769,7 +783,7 @@ Evaluation suites and label sets built on top of the raw datasets above.
 | [TAVIS](https://arxiv.org/abs/2605.07943) | 2026-05 | arXiv | IsaacLab active-vision imitation tasks | Headcam vs fixed-cam evaluation, wrist/head active vision, and anticipatory-gaze metric | watch |
 | [MM-Conv](https://arxiv.org/abs/2605.21796) | 2026-05 | arXiv | 6.7 hours of egocentric VR interaction | Referential communication with speech, motion, gaze, and 3D scenes | watch |
 | [EgoExoMem](https://arxiv.org/abs/2605.18734) | 2026-05 | arXiv | Synchronized ego-exo videos | Cross-view memory QA | watch |
-| [EgoMemReason](https://arxiv.org/abs/2605.09874) | 2026-05 | arXiv | Week-long egocentric video | Entity, event, and behavior memory reasoning | watch |
+| [EgoMemReason](https://huggingface.co/datasets/Ted412/EgoMemReason) | 2026-05 | COLM 2026 | Week-long EgoLife video; 500 public questions plus evaluation code and leaderboard | Entity, event, and behavior memory reasoning | open |
 | [Personal Visual Context Learning / Personal-VCL-Bench](https://vision.cs.utexas.edu/projects/PersonalVCL/) | 2026-05 | arXiv | Continuous smart-glasses streams | Prompt-time wearer-specific visual-context learning for personalized LMM assistants | watch |
 | [GazeMind / CogLoad-Bench](https://arxiv.org/abs/2605.05790) | 2026-05 | arXiv | Smart-glasses gaze and cognitive-load annotations | Gaze-guided LLM agent evaluation for personalized cognitive-load assessment | watch |
 | [VIGIL](https://arxiv.org/abs/2605.08747) | 2026-05 | arXiv | Egocentric RGB embodied-agent episodes | Terminal-commitment scoring that separates world completion from success reporting | watch |
@@ -870,6 +884,7 @@ Open models, baselines, and loaders you can build on directly.
 
 | Resource | Released | Venue | What it contributes | Link |
 | :--- | :---: | :---: | :--- | :---: |
+| EgoPlay | 2026-07 | SIGGRAPH Asia 2026 | Event-triggered egocentric video editing trained on 106K clip-prompt pairs, jointly learning trigger recognition, temporal restraint, and post-event editing | [Project](https://egoplay2026.github.io/egoplay/) |
 | VideoTreeSearch | 2026-07 | arXiv | Self-correcting temporal-tree agent for grounded long-video QA, with MIT-licensed inference/SFT/RL code, an 8B checkpoint, and released Haystack-Ego4D trajectories/evaluation data | [GitHub](https://github.com/CeeZh/VTS) |
 | OmniView-Space | 2026-07 | arXiv | Tool-guided egocentric spatial reasoning with query-aligned visual cognitive maps, textual spatial graphs, and ego-frame rewards | [Paper](https://arxiv.org/abs/2607.00881) |
 | CGGS | 2026-07 | arXiv | Text-to-3D ego-centric scene generation with consistency-augmented 2D priors, point-track/depth layout decoration, and geometric Gaussian refinement | [Paper](https://arxiv.org/abs/2607.03819) |
@@ -1176,6 +1191,9 @@ These resources are **not first-person/egocentric**, but they are close neighbor
 
 | Resource | Released | Venue | Scale / signal | Why it is adjacent (not egocentric) | Status |
 | :--- | :---: | :---: | :--- | :--- | :---: |
+| [Data Pyramid for Embodied Manipulation](https://jasper-aaa.github.io/embodied-data-pyramid/) | 2026-07 | arXiv | Open survey and living catalog organizing real-robot, UMI, human ego/ego-exo, simulation, and general video data into five levels | Broad embodied-manipulation taxonomy in which egocentric data is one major layer | open |
+| [ContactFlow](https://arxiv.org/abs/2607.26579) | 2026-07 | arXiv | Embodiment-agnostic world-model conditioning through trajectories of 3D actor-object contact points, trained with human and robot interaction video | General human/robot video; wearable capture is not required | watch |
+| [Robot-Factored World Models](https://bjkim95.github.io/rofacto/) | 2026-07 | arXiv | Factors actions into nominal robot trajectories and rendered geometry across DROID, egocentric RoboCasa-GR1, unseen robots, and retargeted human demos | Robot-camera world model rather than human wearable capture | watch |
 | [AWM Navigation Pretraining Corpus](https://huggingface.co/datasets/Yangyihui/awm-nav-pretrain) | 2026-07 | Hugging Face | Public 198.1 GB corpus with 23,076 indoor/outdoor robot-view clips and paired Gemini-generated spatial/action labels; source-derived reuse terms are incomplete | Robot navigation observations rather than human wearable capture | partial |
 | [Think at 5 Hz, Act at 20 Hz](https://arxiv.org/abs/2607.15621) | 2026-07 | arXiv | Asynchronous driving VLA with a frozen 7B reasoner and fast action expert, raising CARLA route completion from 37.0 to 94.0 at fresh 20 Hz control | Autonomous-driving camera input rather than human wearable capture | watch |
 | [IMBench](https://imbench.org/) | 2026-07 | RSS 2026 SemRob Workshop | Open benchmark with 35 tasks, seven categories, and 14K trajectories integrating physical reasoning with executable manipulation | Robot-manipulation benchmark rather than human wearable capture | open |

README.pt.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>Conjuntos de dados, benchmarks, modelos e ferramentas para visão egocêntrica, IA incorporada e robótica, vídeo-linguagem, memória de longo contexto, RA/RV e interação mão-objeto.</strong></p>
 
-<p align="center"><strong>793</strong> recursos egocêntricos — 202 conjuntos de dados · 134 benchmarks · 412 modelos · 40 ferramentas</p>
+<p align="center"><strong>808</strong> recursos egocêntricos — 208 conjuntos de dados · 137 benchmarks · 415 modelos · 42 ferramentas</p>
 
 ## O que inclui
 

README.zh.md

@@ -20,7 +20,7 @@
 
 <p align="center"><strong>用于自我中心视觉、具身智能与机器人、视频语言、长上下文记忆、AR/VR 和手物交互的数据集、基准、模型与工具。</strong></p>
 
-<p align="center"><strong>793</strong> 自我中心资源 — 202 数据集 · 134 基准 · 412 模型 · 40 工具包</p>
+<p align="center"><strong>808</strong> 自我中心资源 — 208 数据集 · 137 基准 · 415 模型 · 42 工具包</p>
 
 ## 内容概览
 

awesome-egocentric-atlas.csv

@@ -1,6 +1,24 @@
 name,kind,released,venue,status,scope,year,url,paper,code,license,scale,tasks,modalities
 Xperience-10M,dataset,2026-03,Hugging Face,request,,2026,https://huggingface.co/datasets/ropedia-ai/xperience-10m,,,other,"10M experiences, 10K hours, six video streams, audio, stereo depth, camera pose, hand/body mocap, IMU, hierarchical language, about 1 PB total",embodied-ai; world-modeling; robot-learning; sensor-fusion; 3d-4d-understanding; imitation-learning,fisheye-video; stereo-video; audio; stereo-depth; camera-pose; hand-mocap; full-body-mocap; imu; hierarchical-language
 Xperience-10M Sample,dataset,2026-03,Hugging Face,open,,2026,https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample,,,cc-by-nc-4.0,Public sample episode; Hugging Face viewer reports 6 rows,sample-data; loader-testing; visualization; task-suite-prototyping,video; hdf5-annotations
+ReViV,model,2026-07,ECCV 2026,open,,2026,https://reviv4d.github.io/,https://arxiv.org/abs/2607.17790,https://github.com/lvsean/reviv4d,Apache-2.0 code; non-commercial checkpoint terms,"Unified feed-forward monocular egocentric 4D reconstruction of RGB, camera trajectory, gaze, body, hands, and depth; evaluated on HoloAssist, HOT3D, ARCTIC, Aria Digital Twin, TACO, and pretrained on more than 600 hours",4d-reconstruction; camera-tracking; egocentric-3d-pose; gaze-estimation; depth-estimation,egocentric-video; camera-pose; gaze; body-pose; hand-pose; depth
+EgoRecovery,model,2026-07,arXiv,watch,,2026,https://arxiv.org/abs/2607.19745,https://arxiv.org/abs/2607.19745,,,Co-training framework that aligns egocentric human failure-recovery demonstrations with a corrective-intent space and a small robot-data anchor; its collection protocol yields more than 10x as much valid recovery data per hour as robot teleoperation,failure-recovery; robot-learning; imitation-learning; human-to-robot-transfer,egocentric-video; human-demonstrations; robot-actions
+Sidewalk Moments,dataset,2026-07,arXiv,watch,,2026,https://arxiv.org/abs/2607.20903,https://arxiv.org/abs/2607.20903,,,"61 first-person YouTube city-walk videos segmented into more than 50,000 ten-second clips with video, temporally averaged image, audio, and text representations for human-aligned urban-engagement analysis",urban-understanding; human-alignment; multimodal-representation; engagement-prediction,egocentric-video; audio; natural-language; image
+CRAFT Wearable Creative AI,toolkit,2026-07,arXiv,watch,,2026,https://arxiv.org/abs/2607.21394,https://arxiv.org/abs/2607.21394,,,"Context-aware smart-glasses creative-AI probe studied through nine writer interviews, co-design with 16 writers and researchers, and 24 real-world sessions with eight writers",wearable-ai; context-aware-assistance; human-computer-interaction; creativity-support,smart-glasses; egocentric-video; natural-language
+SHARE User-Centric AR SLAM,toolkit,2026-07,arXiv,watch,,2026,https://arxiv.org/abs/2607.23901,https://arxiv.org/abs/2607.23901,,,"User-prioritized edge SLAM for commercial head-mounted AR and a ground robot in shared workspaces; reports 13.22 ms average AR latency, a 43.3% reduction, while maintaining sub-2-centimeter tracking",ar-vr; slam; human-robot-collaboration; localization,ar-headset; egocentric-video; robot-video; camera-pose
+EgoPlay,model,2026-07,SIGGRAPH Asia 2026,partial,,2026,https://egoplay2026.github.io/egoplay/,https://arxiv.org/abs/2607.24560,,,"Event-triggered egocentric video-to-video editing trained on 106K clip-prompt pairs, primarily from Ego4D, with positive, negative, and multi-event triggers plus event-aware evaluation",video-editing; event-detection; video-generation; streaming-video,egocentric-video; natural-language; generated-video
+Data Pyramid for Embodied Manipulation,survey,2026-07,arXiv,open,adjacent,2026,https://jasper-aaa.github.io/embodied-data-pyramid/,https://arxiv.org/abs/2607.24744,https://github.com/worldbench/awesome-embodied-data-pyramid,apache-2.0,"Survey and living catalog organizing real-robot, UMI, human egocentric and ego-exo, simulation, and general video data into a five-level embodied-manipulation data pyramid",survey; data-curation; robot-manipulation; embodied-ai,
+HiFi-UMI-2K,dataset,2026-07,arXiv,open,,2026,https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K,https://arxiv.org/abs/2607.25895,,cc-by-4.0,"2,000 hours of public robot-free manipulation demonstrations from a high-fidelity UMI rig with head stereo-inertial SLAM, native inter-gripper pose, microsecond GPIO synchronization, and two roughly 200-degree cameras per hand; reports 3 mm local end-effector accuracy",robot-learning; imitation-learning; vision-language-action; world-action-model; human-to-robot-transfer,egocentric-video; stereo-video; wrist-video; camera-pose; gripper-pose; imu; robot-actions
+EgoSafe-Bench,benchmark,2026-07,arXiv,watch,,2026,https://arxiv.org/abs/2607.26518,https://arxiv.org/abs/2607.26518,,,"12,000 safety-reasoning evaluation samples formed from 3,000 first-person mobile-captured clips and hierarchical QA chains spanning evidence anchoring, blind-spot deduction, intent inference, and causal consistency",safety-reasoning; video-qa; causal-reasoning; benchmark,egocentric-video; video-qa; natural-language
+HumanCLAW-Bench,benchmark,2026-07,arXiv,watch,,2026,https://human-claw.github.io/,https://arxiv.org/abs/2607.27180,https://github.com/Human-CLAW/HumanCLAW,,"1,218 long-horizon egocentric find-navigate-interact episodes across 41 indoor scenes, evaluating nine VLMs through atomic full-body skill commands; the best reported success rate is 16.8%",embodied-reasoning; navigation; interaction; body-awareness; benchmark,egocentric-video; body-pose; natural-language; embodied-actions
+DDD Egocentric Stereo Manipulation Sample,dataset,2026-07,Hugging Face,open,,2026,https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset,,,cc-by-4.0,"Ten public LeRobot v2 episodes totaling about 2.37 GB with synchronized left/right egocentric video, high-frequency hand and head pose, and task/episode metadata",robot-learning; imitation-learning; hand-object-interaction; sensor-fusion,egocentric-video; stereo-video; hand-pose; head-pose; natural-language
+Showway Egocentric Origami Series,collection,2026-07,Hugging Face,open,,2026,https://huggingface.co/datasets/showway-ego/egocentric-origami-001,,,apache-2.0,"Three public LeRobot v3 repositories with nine neck-mounted iPhone ultra-wide origami episodes, HaMeR-derived 3D hand joints, video, and human-reviewed narration",hand-object-interaction; procedure-understanding; imitation-learning; robot-learning,egocentric-video; hand-pose; natural-language
+EGXO Household Egocentric Video Evaluation,dataset,2026-07,Hugging Face,request,,2026,https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation,,,other,71 household-task videos totaling exactly 10 hours and about 43.4 GiB; six preview clips and task metadata are publicly visible while the complete media package requires a commercial data license,household-activity; procedure-understanding; robot-learning; hand-object-interaction,egocentric-video; natural-language; metadata
+Egocentric Hand Benchmark Annotations,benchmark,2026-07,Hugging Face,partial,,2026,https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark,,,other,"100,427 public annotation rows: 95,002 EgoDaily hand boxes and 5,425 HOT3D virtual hand-crop camera records, distributed without the source RGB",hand-detection; hand-tracking; hand-pose-estimation; benchmark,hand-bounding-boxes; camera-pose; annotations
+ChildLens,dataset,2026-04,Behavior Research Methods 2026,request,,2026,https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/,https://doi.org/10.3758/s13428-026-02982-6,https://github.com/neleSuffo/ChildLens,other,"109 hours of vest-mounted 140-degree egocentric video and audio from 62 children aged 3 to 5 in their homes, with five location classes and 14 exhaustively annotated activity classes",child-development; activity-recognition; temporal-localization; voice-type-classification,egocentric-video; audio; natural-language; annotations
+HuMI,dataset,2026-02,arXiv,open,,2026,https://humanoid-manipulation-interface.github.io/,https://arxiv.org/abs/2602.06643,https://github.com/Richard-coder-Nai/HuMI,MIT code; CC-BY-4.0 datasets,"Portable robot-free whole-body demonstration interface and seven-dataset Hugging Face collection spanning five kneeling, squatting, tossing, walking, and bimanual tasks; reports 3x collection efficiency and 70% unseen-environment success",humanoid-manipulation; whole-body-control; imitation-learning; human-to-robot-transfer,egocentric-video; wrist-video; body-pose; hand-pose; robot-actions
+ContactFlow,model,2026-07,arXiv,watch,adjacent,2026,https://arxiv.org/abs/2607.26579,https://arxiv.org/abs/2607.26579,,,"Embodiment-agnostic video action conditioning through trajectories of 3D actor-object contact points, trained with human and robot interactions and evaluated on DROID and real tabletop tasks",world-modeling; human-to-robot-transfer; contact-reasoning; robot-manipulation,human-video; robot-video; 3d-contact; generated-video
+Robot-Factored World Models,model,2026-07,arXiv,watch,adjacent,2026,https://bjkim95.github.io/rofacto/,https://arxiv.org/abs/2607.22535,https://github.com/bjkim95/rofacto,,"Action-conditioned world model that factors robot control and appearance into nominal trajectories and rendered robot geometry, evaluated on DROID and egocentric RoboCasa-GR1 with zero-shot embodiments and human-demo retargeting",world-modeling; robot-manipulation; cross-embodiment-transfer; video-generation,robot-video; depth; robot-actions; generated-video
 EgoExoMoCap,model,2026-07,ECCV 2026,watch,,2026,https://arxiv.org/abs/2607.15868,https://arxiv.org/abs/2607.15868,,,Distributed human-motion capture in which two or more people wear smart glasses; fuses head and optional wrist tracking with DINOv3 image features and is evaluated on two in-the-wild ego-exo datasets,egocentric-3d-pose; human-motion; ego-exo; human-pose-estimation,hmd-video; exocentric-video; head-pose; wrist-trajectory; body-pose
 Exo2EgoPose,model,2026-07,ACM MM 2026,watch,,2026,https://arxiv.org/abs/2607.15890,https://arxiv.org/abs/2607.15890,,,"Vision-language-guided egocentric 3D hand-pose forecasting that reconstructs exocentric demonstrations to guide ego-view prediction, evaluated on AssemblyHands, Ego-Exo4D, EgoMe-pose, and CALVIN transfer",3d-hand-trajectory-forecasting; hand-forecasting; ego-exo; cross-embodiment-transfer,egocentric-video; exocentric-video; 3d-hand-pose; language-instructions
 Let the Body Follow,toolkit,2026-07,arXiv,watch,,2026,https://arxiv.org/abs/2607.16095,https://arxiv.org/abs/2607.16095,,,Coupled egocentric whole-body teleoperation for TIAGo in which head and arm motion automatically coordinate torso and mobile-base control; evaluated in a home-care-inspired user study,digital-teleoperation; whole-body-control; human-robot-interaction; mobile-manipulation,hmd-video; head-pose; hand-pose; robot-actions
@@ -423,7 +441,7 @@ Ego-EXTRA,dataset,2025-12,WACV 2026,open,,2025,https://fpv-iplab.github.io/Ego-E
 EgoSchema,benchmark,2023-08,NeurIPS 2023,open,,2023,http://egoschema.github.io/,https://arxiv.org/abs/2308.09126,https://github.com/egoschema/EgoSchema,,"5K+ multiple-choice QA pairs, 250+ hours",long-video-qa; temporal-reasoning,
 X-LeBench,benchmark,2025-01,EMNLP 2025,watch,,2025,https://arxiv.org/abs/2501.06835,https://arxiv.org/abs/2501.06835,,,"432 simulated life logs, 23 minutes to 16.4 hours",extremely-long-video-understanding; lifelogging; long-context-qa,
 TeleEgo,benchmark,2025-10,arXiv,watch,,2025,https://arxiv.org/abs/2510.23981,https://arxiv.org/abs/2510.23981,,,"3,291 human-verified QA items in streaming setting",streaming-assistant; memory; real-time-understanding; cross-memory-reasoning,egocentric-video; audio; text; timeline
-EgoMemReason,benchmark,2026-05,arXiv,watch,,2026,https://arxiv.org/abs/2605.09874,https://arxiv.org/abs/2605.09874,,,"500 questions across entity, event, and behavior memory; average 25.9 hours of memory backtracking",long-horizon-memory; entity-memory; event-memory; behavior-memory; egocentric-video-reasoning,
+EgoMemReason,benchmark,2026-05,COLM 2026,open,,2026,https://huggingface.co/datasets/Ted412/EgoMemReason,https://arxiv.org/abs/2605.09874,https://github.com/Ziyang412/EgoMemReason,cc-by-nc-4.0,"500 public multiple-choice questions over week-long EgoLife video across entity, event, and behavior memory; average 5.1 evidence segments and 25.9 hours of memory backtracking",long-horizon-memory; entity-memory; event-memory; behavior-memory; egocentric-video-reasoning,
 EgoClip,dataset,2022-06,NeurIPS 2022,open,,2022,https://github.com/showlab/EgoVLP,https://arxiv.org/abs/2206.01670,,not specified,3.8M clip-text pairs,video-language-pretraining; retrieval,
 RefEgo,benchmark,2023-08,ICCV 2023,open,,2023,https://github.com/shuheikurita/RefEgo,https://arxiv.org/abs/2308.12035,,,12K+ clips and 41 hours for video-based referring-expression comprehension,referring-expression-comprehension; object-grounding; referred-object-tracking,
 EgoBench,benchmark,2026-05,arXiv,watch,,2026,https://arxiv.org/abs/2605.27820,https://arxiv.org/abs/2605.27820,,,"1,045 egocentric-video-grounded interactive tasks",tool-using-agents; multimodal-reasoning; interaction,
@@ -571,7 +589,7 @@ EgoVid-5M,dataset,2024-11,NeurIPS 2025,open,,2024,https://egovid.github.io/,http
 AoE,dataset,2026-02,arXiv,watch,,2026,https://arxiv.org/abs/2602.23893,https://arxiv.org/abs/2602.23893,,,Always-on egocentric human video collection pipeline and corpus for embodied AI data scaling,robot-learning; data-collection; embodied-ai,
 Seeing Across Views (MV-RoboBench),benchmark,2025-10,ICLR 2026,open,adjacent,2025,https://github.com/microsoft/MV-RoboBench,https://arxiv.org/abs/2510.19400,,,MV-RoboBench: 1.7K curated QA items over eight subtasks testing multi-view spatial reasoning of VLMs in robotic manipulation scenes (ICLR 2026),multi-view; robot-manipulation; vlm-evaluation,
 EgoGesture,dataset,2017-01,IEEE TMM 2018,open,,2017,https://ieeexplore.ieee.org/document/8299578/,,,not specified,"24K+ gesture samples, 3M RGB-D frames, 50 subjects, 83 static and dynamic gestures across six indoor/outdoor scenes",gesture-recognition; hand; wearable-interaction,
-EgoBrain,dataset,2025-06,arXiv,watch,,2025,https://arxiv.org/abs/2506.01353,https://arxiv.org/abs/2506.01353,,,Synchronized EEG and egocentric video for human action understanding from minds and eyes,eeg; action-understanding; multimodal,
+EgoBrain,dataset,2025-06,ICLR 2026,request,,2025,https://huggingface.co/datasets/ut-vision/EgoBrain,https://arxiv.org/abs/2506.01353,,cc-by-nc-4.0,"Complete 1.6 TB release from 40 participants with synchronized 4K GoPro egocentric video, EEG, IMU, interval markers, and surveys for human action understanding",eeg; action-understanding; multimodal,egocentric-video; eeg; imu; natural-language; annotations
 MM-Ego,model,2024-10,ICLR 2025,open,,2024,https://arxiv.org/abs/2410.07177,https://arxiv.org/abs/2410.07177,,,"Egocentric multimodal LLM with Memory Pointer Prompting; 7M-sample QA data engine and the EgoMemoria benchmark (629 videos, 7,026 questions)",video-language; memory; qa,
 EgoStream,benchmark,2026-05,arXiv,watch,,2026,https://arxiv.org/abs/2605.31557,https://arxiv.org/abs/2605.31557,,,"2,250 questions across seven memory dimensions with Answer Validity Windows, expanded to 8,528 recall-conditioned evaluations over streams up to 45.3 hours",streaming-memory; episodic-memory; qa,
 EgoMemory,benchmark,2025-09,OpenReview,watch,,2025,https://openreview.net/forum?id=T0em4hJCQb,,,,"165,795 user-specific object annotations over 245 videos from 45 participants for memory-augmented personalized retrieval",personalized-retrieval; episodic-memory; long-context,

awesome-egocentric-papers.csv

@@ -1,4 +1,18 @@
 name,kind,released,venue,status,scope,year,paper,url,code,license,scale,tasks,modalities
+ReViV,model,2026-07,ECCV 2026,open,egocentric,2026,https://arxiv.org/abs/2607.17790,https://reviv4d.github.io/,https://github.com/lvsean/reviv4d,Apache-2.0 code; non-commercial checkpoint terms,"Unified feed-forward monocular egocentric 4D reconstruction of RGB, camera trajectory, gaze, body, hands, and depth; evaluated on HoloAssist, HOT3D, ARCTIC, Aria Digital Twin, TACO, and pretrained on more than 600 hours",4d-reconstruction; camera-tracking; egocentric-3d-pose; gaze-estimation; depth-estimation,egocentric-video; camera-pose; gaze; body-pose; hand-pose; depth
+EgoRecovery,model,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.19745,https://arxiv.org/abs/2607.19745,,,Co-training framework that aligns egocentric human failure-recovery demonstrations with a corrective-intent space and a small robot-data anchor; its collection protocol yields more than 10x as much valid recovery data per hour as robot teleoperation,failure-recovery; robot-learning; imitation-learning; human-to-robot-transfer,egocentric-video; human-demonstrations; robot-actions
+Sidewalk Moments,dataset,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.20903,https://arxiv.org/abs/2607.20903,,,"61 first-person YouTube city-walk videos segmented into more than 50,000 ten-second clips with video, temporally averaged image, audio, and text representations for human-aligned urban-engagement analysis",urban-understanding; human-alignment; multimodal-representation; engagement-prediction,egocentric-video; audio; natural-language; image
+CRAFT Wearable Creative AI,toolkit,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.21394,https://arxiv.org/abs/2607.21394,,,"Context-aware smart-glasses creative-AI probe studied through nine writer interviews, co-design with 16 writers and researchers, and 24 real-world sessions with eight writers",wearable-ai; context-aware-assistance; human-computer-interaction; creativity-support,smart-glasses; egocentric-video; natural-language
+SHARE User-Centric AR SLAM,toolkit,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.23901,https://arxiv.org/abs/2607.23901,,,"User-prioritized edge SLAM for commercial head-mounted AR and a ground robot in shared workspaces; reports 13.22 ms average AR latency, a 43.3% reduction, while maintaining sub-2-centimeter tracking",ar-vr; slam; human-robot-collaboration; localization,ar-headset; egocentric-video; robot-video; camera-pose
+EgoPlay,model,2026-07,SIGGRAPH Asia 2026,partial,egocentric,2026,https://arxiv.org/abs/2607.24560,https://egoplay2026.github.io/egoplay/,,,"Event-triggered egocentric video-to-video editing trained on 106K clip-prompt pairs, primarily from Ego4D, with positive, negative, and multi-event triggers plus event-aware evaluation",video-editing; event-detection; video-generation; streaming-video,egocentric-video; natural-language; generated-video
+Data Pyramid for Embodied Manipulation,survey,2026-07,arXiv,open,adjacent,2026,https://arxiv.org/abs/2607.24744,https://jasper-aaa.github.io/embodied-data-pyramid/,https://github.com/worldbench/awesome-embodied-data-pyramid,apache-2.0,"Survey and living catalog organizing real-robot, UMI, human egocentric and ego-exo, simulation, and general video data into a five-level embodied-manipulation data pyramid",survey; data-curation; robot-manipulation; embodied-ai,
+HiFi-UMI-2K,dataset,2026-07,arXiv,open,egocentric,2026,https://arxiv.org/abs/2607.25895,https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K,,cc-by-4.0,"2,000 hours of public robot-free manipulation demonstrations from a high-fidelity UMI rig with head stereo-inertial SLAM, native inter-gripper pose, microsecond GPIO synchronization, and two roughly 200-degree cameras per hand; reports 3 mm local end-effector accuracy",robot-learning; imitation-learning; vision-language-action; world-action-model; human-to-robot-transfer,egocentric-video; stereo-video; wrist-video; camera-pose; gripper-pose; imu; robot-actions
+EgoSafe-Bench,benchmark,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.26518,https://arxiv.org/abs/2607.26518,,,"12,000 safety-reasoning evaluation samples formed from 3,000 first-person mobile-captured clips and hierarchical QA chains spanning evidence anchoring, blind-spot deduction, intent inference, and causal consistency",safety-reasoning; video-qa; causal-reasoning; benchmark,egocentric-video; video-qa; natural-language
+HumanCLAW-Bench,benchmark,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.27180,https://human-claw.github.io/,https://github.com/Human-CLAW/HumanCLAW,,"1,218 long-horizon egocentric find-navigate-interact episodes across 41 indoor scenes, evaluating nine VLMs through atomic full-body skill commands; the best reported success rate is 16.8%",embodied-reasoning; navigation; interaction; body-awareness; benchmark,egocentric-video; body-pose; natural-language; embodied-actions
+ChildLens,dataset,2026-04,Behavior Research Methods 2026,request,egocentric,2026,https://doi.org/10.3758/s13428-026-02982-6,https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/,https://github.com/neleSuffo/ChildLens,other,"109 hours of vest-mounted 140-degree egocentric video and audio from 62 children aged 3 to 5 in their homes, with five location classes and 14 exhaustively annotated activity classes",child-development; activity-recognition; temporal-localization; voice-type-classification,egocentric-video; audio; natural-language; annotations
+HuMI,dataset,2026-02,arXiv,open,egocentric,2026,https://arxiv.org/abs/2602.06643,https://humanoid-manipulation-interface.github.io/,https://github.com/Richard-coder-Nai/HuMI,MIT code; CC-BY-4.0 datasets,"Portable robot-free whole-body demonstration interface and seven-dataset Hugging Face collection spanning five kneeling, squatting, tossing, walking, and bimanual tasks; reports 3x collection efficiency and 70% unseen-environment success",humanoid-manipulation; whole-body-control; imitation-learning; human-to-robot-transfer,egocentric-video; wrist-video; body-pose; hand-pose; robot-actions
+ContactFlow,model,2026-07,arXiv,watch,adjacent,2026,https://arxiv.org/abs/2607.26579,https://arxiv.org/abs/2607.26579,,,"Embodiment-agnostic video action conditioning through trajectories of 3D actor-object contact points, trained with human and robot interactions and evaluated on DROID and real tabletop tasks",world-modeling; human-to-robot-transfer; contact-reasoning; robot-manipulation,human-video; robot-video; 3d-contact; generated-video
+Robot-Factored World Models,model,2026-07,arXiv,watch,adjacent,2026,https://arxiv.org/abs/2607.22535,https://bjkim95.github.io/rofacto/,https://github.com/bjkim95/rofacto,,"Action-conditioned world model that factors robot control and appearance into nominal trajectories and rendered robot geometry, evaluated on DROID and egocentric RoboCasa-GR1 with zero-shot embodiments and human-demo retargeting",world-modeling; robot-manipulation; cross-embodiment-transfer; video-generation,robot-video; depth; robot-actions; generated-video
 EgoExoMoCap,model,2026-07,ECCV 2026,watch,egocentric,2026,https://arxiv.org/abs/2607.15868,https://arxiv.org/abs/2607.15868,,,Distributed human-motion capture in which two or more people wear smart glasses; fuses head and optional wrist tracking with DINOv3 image features and is evaluated on two in-the-wild ego-exo datasets,egocentric-3d-pose; human-motion; ego-exo; human-pose-estimation,hmd-video; exocentric-video; head-pose; wrist-trajectory; body-pose
 Exo2EgoPose,model,2026-07,ACM MM 2026,watch,egocentric,2026,https://arxiv.org/abs/2607.15890,https://arxiv.org/abs/2607.15890,,,"Vision-language-guided egocentric 3D hand-pose forecasting that reconstructs exocentric demonstrations to guide ego-view prediction, evaluated on AssemblyHands, Ego-Exo4D, EgoMe-pose, and CALVIN transfer",3d-hand-trajectory-forecasting; hand-forecasting; ego-exo; cross-embodiment-transfer,egocentric-video; exocentric-video; 3d-hand-pose; language-instructions
 Let the Body Follow,toolkit,2026-07,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2607.16095,https://arxiv.org/abs/2607.16095,,,Coupled egocentric whole-body teleoperation for TIAGo in which head and arm motion automatically coordinate torso and mobile-base control; evaluated in a home-care-inspired user study,digital-teleoperation; whole-body-control; human-robot-interaction; mobile-manipulation,hmd-video; head-pose; hand-pose; robot-actions
@@ -371,7 +385,7 @@ Ego-EXTRA,dataset,2025-12,WACV 2026,open,egocentric,2025,https://arxiv.org/abs/2
 EgoSchema,benchmark,2023-08,NeurIPS 2023,open,egocentric,2023,https://arxiv.org/abs/2308.09126,http://egoschema.github.io/,https://github.com/egoschema/EgoSchema,,"5K+ multiple-choice QA pairs, 250+ hours",long-video-qa; temporal-reasoning,
 X-LeBench,benchmark,2025-01,EMNLP 2025,watch,egocentric,2025,https://arxiv.org/abs/2501.06835,https://arxiv.org/abs/2501.06835,,,"432 simulated life logs, 23 minutes to 16.4 hours",extremely-long-video-understanding; lifelogging; long-context-qa,
 TeleEgo,benchmark,2025-10,arXiv,watch,egocentric,2025,https://arxiv.org/abs/2510.23981,https://arxiv.org/abs/2510.23981,,,"3,291 human-verified QA items in streaming setting",streaming-assistant; memory; real-time-understanding; cross-memory-reasoning,egocentric-video; audio; text; timeline
-EgoMemReason,benchmark,2026-05,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2605.09874,https://arxiv.org/abs/2605.09874,,,"500 questions across entity, event, and behavior memory; average 25.9 hours of memory backtracking",long-horizon-memory; entity-memory; event-memory; behavior-memory; egocentric-video-reasoning,
+EgoMemReason,benchmark,2026-05,COLM 2026,open,egocentric,2026,https://arxiv.org/abs/2605.09874,https://huggingface.co/datasets/Ted412/EgoMemReason,https://github.com/Ziyang412/EgoMemReason,cc-by-nc-4.0,"500 public multiple-choice questions over week-long EgoLife video across entity, event, and behavior memory; average 5.1 evidence segments and 25.9 hours of memory backtracking",long-horizon-memory; entity-memory; event-memory; behavior-memory; egocentric-video-reasoning,
 EgoClip,dataset,2022-06,NeurIPS 2022,open,egocentric,2022,https://arxiv.org/abs/2206.01670,https://github.com/showlab/EgoVLP,,not specified,3.8M clip-text pairs,video-language-pretraining; retrieval,
 RefEgo,benchmark,2023-08,ICCV 2023,open,egocentric,2023,https://arxiv.org/abs/2308.12035,https://github.com/shuheikurita/RefEgo,,,12K+ clips and 41 hours for video-based referring-expression comprehension,referring-expression-comprehension; object-grounding; referred-object-tracking,
 EgoBench,benchmark,2026-05,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2605.27820,https://arxiv.org/abs/2605.27820,,,"1,045 egocentric-video-grounded interactive tasks",tool-using-agents; multimodal-reasoning; interaction,
@@ -500,7 +514,7 @@ EgoObjects API,toolkit,2023-09,ICCV 2023,open,egocentric,2023,https://arxiv.org/
 EgoVid-5M,dataset,2024-11,NeurIPS 2025,open,egocentric,2024,https://arxiv.org/abs/2411.08380,https://egovid.github.io/,,not specified,5M curated egocentric clips at 1080p with fine-grained kinematic and high-level textual action annotations (NeurIPS 2025),video-generation; world-modeling; action-conditioned-generation,
 AoE,dataset,2026-02,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2602.23893,https://arxiv.org/abs/2602.23893,,,Always-on egocentric human video collection pipeline and corpus for embodied AI data scaling,robot-learning; data-collection; embodied-ai,
 Seeing Across Views (MV-RoboBench),benchmark,2025-10,ICLR 2026,open,adjacent,2025,https://arxiv.org/abs/2510.19400,https://github.com/microsoft/MV-RoboBench,,,MV-RoboBench: 1.7K curated QA items over eight subtasks testing multi-view spatial reasoning of VLMs in robotic manipulation scenes (ICLR 2026),multi-view; robot-manipulation; vlm-evaluation,
-EgoBrain,dataset,2025-06,arXiv,watch,egocentric,2025,https://arxiv.org/abs/2506.01353,https://arxiv.org/abs/2506.01353,,,Synchronized EEG and egocentric video for human action understanding from minds and eyes,eeg; action-understanding; multimodal,
+EgoBrain,dataset,2025-06,ICLR 2026,request,egocentric,2025,https://arxiv.org/abs/2506.01353,https://huggingface.co/datasets/ut-vision/EgoBrain,,cc-by-nc-4.0,"Complete 1.6 TB release from 40 participants with synchronized 4K GoPro egocentric video, EEG, IMU, interval markers, and surveys for human action understanding",eeg; action-understanding; multimodal,egocentric-video; eeg; imu; natural-language; annotations
 MM-Ego,model,2024-10,ICLR 2025,open,egocentric,2024,https://arxiv.org/abs/2410.07177,https://arxiv.org/abs/2410.07177,,,"Egocentric multimodal LLM with Memory Pointer Prompting; 7M-sample QA data engine and the EgoMemoria benchmark (629 videos, 7,026 questions)",video-language; memory; qa,
 EgoStream,benchmark,2026-05,arXiv,watch,egocentric,2026,https://arxiv.org/abs/2605.31557,https://arxiv.org/abs/2605.31557,,,"2,250 questions across seven memory dimensions with Answer Validity Windows, expanded to 8,528 recall-conditioned evaluations over streams up to 45.3 hours",streaming-memory; episodic-memory; qa,
 Gesture-Based Egocentric Video QA,benchmark,2026-03,CVPR 2026,watch,egocentric,2026,https://arxiv.org/abs/2603.12533,https://arxiv.org/abs/2603.12533,,,Egocentric video QA grounded in the camera wearer's pointing and deictic gestures,gesture-grounding; qa; referential,

data/resources.yml

@@ -1,7 +1,7 @@
 meta:
   title: Awesome Egocentric Atlas
   description: "Awesome Egocentric Atlas is a catalog of egocentric AI resources for egocentric vision, embodied AI, robotics, VLA, world models, WMA, memory, AR/VR, and hand-object interaction."
-  last_major_audit: "2026-07-20"
+  last_major_audit: "2026-07-30"
   scope: Egocentric, first-person, wearable-camera, AR/VR headset, body/wrist camera, and ego-exo datasets, benchmarks, models, and tools.
   status_legend:
     open: Public download, public annotations, public code, or application-based access is clearly documented.
@@ -48,6 +48,340 @@ resources:
     license_url: "https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample"
     verified_at: "2026-06-20"
 
+  # --- Full live scan additions (2026-07-30): arXiv, project, code, publisher, and Hugging Face sweep ---
+
+  - name: ReViV
+    kind: model
+    released: "2026-07"
+    venue: "ECCV 2026"
+    year: 2026
+    status: open
+    url: https://reviv4d.github.io/
+    project: https://reviv4d.github.io/
+    paper: https://arxiv.org/abs/2607.17790
+    code: https://github.com/lvsean/reviv4d
+    scale: "Unified feed-forward monocular egocentric 4D reconstruction of RGB, camera trajectory, gaze, body, hands, and depth; evaluated on HoloAssist, HOT3D, ARCTIC, Aria Digital Twin, TACO, and pretrained on more than 600 hours"
+    modalities: [egocentric-video, camera-pose, gaze, body-pose, hand-pose, depth]
+    tasks: [4d-reconstruction, camera-tracking, egocentric-3d-pose, gaze-estimation, depth-estimation]
+    created_by: "Xiaozhong Lyu, Gen Li, Zhiyin Qian, Xucong Zhang, Marc Pollefeys, and Siyu Tang"
+    license: "Apache-2.0 code; non-commercial checkpoint terms"
+    license_url: https://github.com/lvsean/reviv4d/blob/main/LICENSE
+    verified_at: "2026-07-30"
+    release_note: "The implementation and pretrained checkpoints are public. Code is Apache-2.0; checkpoint use follows the separate non-commercial terms linked by the repository."
+    citation_key: reviv_2026
+
+  - name: EgoRecovery
+    kind: model
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    url: https://arxiv.org/abs/2607.19745
+    paper: https://arxiv.org/abs/2607.19745
+    scale: "Co-training framework that aligns egocentric human failure-recovery demonstrations with a corrective-intent space and a small robot-data anchor; its collection protocol yields more than 10x as much valid recovery data per hour as robot teleoperation"
+    modalities: [egocentric-video, human-demonstrations, robot-actions]
+    tasks: [failure-recovery, robot-learning, imitation-learning, human-to-robot-transfer]
+    created_by: "Zuhao Ge, Yuchen Zhou, Weitao Zhou, Minglei Li, Xinyu Li, Chao Wu, Hanwen Zhao, Haotian Wang, Zuxuan Wu, Xiaosong Jia, and Yu-Gang Jiang"
+    verified_at: "2026-07-30"
+    release_note: "The paper is public, but no project page, code, human-recovery corpus, robot data, or reusable license was linked during this audit."
+    citation_key: egorecovery_2026
+
+  - name: Sidewalk Moments
+    kind: dataset
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    url: https://arxiv.org/abs/2607.20903
+    paper: https://arxiv.org/abs/2607.20903
+    scale: "61 first-person YouTube city-walk videos segmented into more than 50,000 ten-second clips with video, temporally averaged image, audio, and text representations for human-aligned urban-engagement analysis"
+    modalities: [egocentric-video, audio, natural-language, image]
+    tasks: [urban-understanding, human-alignment, multimodal-representation, engagement-prediction]
+    created_by: "Liu Liu, Freya Huying Tan, and Fabio Duarte"
+    verified_at: "2026-07-30"
+    release_note: "The manuscript is under review at Scientific Reports. No public clip list, annotations, extracted features, code, or dataset license was linked."
+    citation_key: sidewalk_moments_2026
+
+  - name: CRAFT Wearable Creative AI
+    kind: toolkit
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    url: https://arxiv.org/abs/2607.21394
+    paper: https://arxiv.org/abs/2607.21394
+    scale: "Context-aware smart-glasses creative-AI probe studied through nine writer interviews, co-design with 16 writers and researchers, and 24 real-world sessions with eight writers"
+    modalities: [smart-glasses, egocentric-video, natural-language]
+    tasks: [wearable-ai, context-aware-assistance, human-computer-interaction, creativity-support]
+    created_by: "Runze Cai, Yuxuan Huang, Lin-Ping Yuan, Kexin Xiang, David Hsu, Collier Nogues, Jussi Holopainen, and Shengdong Zhao"
+    verified_at: "2026-07-30"
+    release_note: "The arXiv record reports conditional PACM IMWUT acceptance pending minor revisions. No reusable prototype, study package, code, or license was linked, so the venue remains arXiv until final publication is verifiable."
+    citation_key: craft_wearable_ai_2026
+
+  - name: SHARE User-Centric AR SLAM
+    kind: toolkit
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    url: https://arxiv.org/abs/2607.23901
+    paper: https://arxiv.org/abs/2607.23901
+    scale: "User-prioritized edge SLAM for commercial head-mounted AR and a ground robot in shared workspaces; reports 13.22 ms average AR latency, a 43.3% reduction, while maintaining sub-2-centimeter tracking"
+    modalities: [ar-headset, egocentric-video, robot-video, camera-pose]
+    tasks: [ar-vr, slam, human-robot-collaboration, localization]
+    created_by: "Tianyuan Du, Tianyi Hu, Hanting Ye, and Maria Gorlatova"
+    verified_at: "2026-07-30"
+    release_note: "The paper and user study are public, but no implementation, system traces, study data, or reusable license was linked."
+    citation_key: share_ar_slam_2026
+
+  - name: EgoPlay
+    kind: model
+    released: "2026-07"
+    venue: "SIGGRAPH Asia 2026"
+    year: 2026
+    status: partial
+    url: https://egoplay2026.github.io/egoplay/
+    project: https://egoplay2026.github.io/egoplay/
+    paper: https://arxiv.org/abs/2607.24560
+    scale: "Event-triggered egocentric video-to-video editing trained on 106K clip-prompt pairs, primarily from Ego4D, with positive, negative, and multi-event triggers plus event-aware evaluation"
+    modalities: [egocentric-video, natural-language, generated-video]
+    tasks: [video-editing, event-detection, video-generation, streaming-video]
+    created_by: "Jinjie Mai, Gordon Guocheng Qian, Willi Menapace, Arpit Sahni, Chaoyang Wang, Ashkan Mirzaei, Runjia Li, Sergey Tulyakov, Bernard Ghanem, Peter Wonka, and Rameen Abdal"
+    verified_at: "2026-07-30"
+    release_note: "The accepted SIGGRAPH Asia 2026 paper and project demonstrations are public. The linked benchmark repository was unavailable during this audit, and no training data, model weights, code, or reusable license could be verified."
+    citation_key: egoplay_2026
+
+  - name: Data Pyramid for Embodied Manipulation
+    kind: survey
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: open
+    scope: adjacent
+    url: https://jasper-aaa.github.io/embodied-data-pyramid/
+    project: https://jasper-aaa.github.io/embodied-data-pyramid/
+    paper: https://arxiv.org/abs/2607.24744
+    code: https://github.com/worldbench/awesome-embodied-data-pyramid
+    scale: "Survey and living catalog organizing real-robot, UMI, human egocentric and ego-exo, simulation, and general video data into a five-level embodied-manipulation data pyramid"
+    tasks: [survey, data-curation, robot-manipulation, embodied-ai]
+    created_by: "Yifan Ye, Yankai Fu, Yaoxu Lv, Bohan Hou, Jun Cen, Lingdong Kong, Duo Zheng, Tianxing Chen, Jiaming Liu, Ziang Cao, Yunfan Lou, Wei Chow, Xian Sun, Yingshuo Wang, Kuangzhi Ge, Xiaowei Chi, Xidong Zhang, Zhibo Pang, Yiwu Zhong, Sirui Han, Zhihe Lu, Weihao Yuan, Qifeng Chen, Michael Yu Wang, Yao Mu, Ziwei Liu, Jianfei Yang, Ping Luo, and Shanghang Zhang"
+    license: apache-2.0
+    license_url: https://github.com/worldbench/awesome-embodied-data-pyramid/blob/main/LICENSE
+    verified_at: "2026-07-30"
+    scope_note: "Broad embodied-manipulation survey in which egocentric and UMI resources are one major layer rather than the exclusive subject."
+    citation_key: embodied_data_pyramid_2026
+
+  - name: HiFi-UMI-2K
+    kind: dataset
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: open
+    url: https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K
+    project: https://cloud.simpleai.tech/simple-world-lab/hifi-umi/
+    paper: https://arxiv.org/abs/2607.25895
+    data: https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K
+    scale: "2,000 hours of public robot-free manipulation demonstrations from a high-fidelity UMI rig with head stereo-inertial SLAM, native inter-gripper pose, microsecond GPIO synchronization, and two roughly 200-degree cameras per hand; reports 3 mm local end-effector accuracy"
+    modalities: [egocentric-video, stereo-video, wrist-video, camera-pose, gripper-pose, imu, robot-actions]
+    tasks: [robot-learning, imitation-learning, vision-language-action, world-action-model, human-to-robot-transfer]
+    created_by: "Simple AI; Yuteng Wei, Jinming Ma, Jiawei Wang, Weitao Zhou, Yushen Zuo, Ke Rui, Minglei Li, Jinhao Zhang, Zhikang Pan, Xiang Wang, Haoran Jia, Huan Du, Zicheng Zeng, Jun Ma, Guiyu Qin, Di Zhang, and Xiaofei Li"
+    released_by: "Simple World Lab"
+    license: cc-by-4.0
+    license_url: https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K/blob/main/README.md
+    verified_at: "2026-07-30"
+    release_note: "The ungated Hugging Face release is public under CC-BY-4.0. The paper distinguishes this 2,000-hour release from the larger internal corpus used in some experiments."
+    citation_key: hifi_umi_2026
+
+  - name: EgoSafe-Bench
+    kind: benchmark
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    url: https://arxiv.org/abs/2607.26518
+    paper: https://arxiv.org/abs/2607.26518
+    scale: "12,000 safety-reasoning evaluation samples formed from 3,000 first-person mobile-captured clips and hierarchical QA chains spanning evidence anchoring, blind-spot deduction, intent inference, and causal consistency"
+    modalities: [egocentric-video, video-qa, natural-language]
+    tasks: [safety-reasoning, video-qa, causal-reasoning, benchmark]
+    created_by: "Yuyun Chen, Tianao Li, TianQuan Feng, Cen Chen, Huiping Zhuang, Hao Peng, and Ziqian Zeng"
+    verified_at: "2026-07-30"
+    release_note: "The paper describes a new benchmark, but no public clips, annotations, evaluation code, project page, or license was linked."
+    citation_key: egosafe_2026
+
+  - name: HumanCLAW-Bench
+    kind: benchmark
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    url: https://human-claw.github.io/
+    project: https://human-claw.github.io/
+    paper: https://arxiv.org/abs/2607.27180
+    code: https://github.com/Human-CLAW/HumanCLAW
+    scale: "1,218 long-horizon egocentric find-navigate-interact episodes across 41 indoor scenes, evaluating nine VLMs through atomic full-body skill commands; the best reported success rate is 16.8%"
+    modalities: [egocentric-video, body-pose, natural-language, embodied-actions]
+    tasks: [embodied-reasoning, navigation, interaction, body-awareness, benchmark]
+    created_by: "Siyao Li, Jiawei Gu, Shuai Liu, Kairui Hu, Zekun Li, Linjie Li, Chengcheng Tang, Po-Chen Wu, Ivan Shugurov, Lingni Ma, Michael Zollhoefer, Sizhe An, Abhay Mittal, Amy Zhao, Ranjay Krishna, Manling Li, Ziwei Liu, and Chuan Guo"
+    verified_at: "2026-07-30"
+    release_note: "The project and placeholder repository are public, but the repository says the code, benchmark, weights, and environment are still being prepared and declares no license."
+    citation_key: humanclaw_2026
+
+  - name: DDD Egocentric Stereo Manipulation Sample
+    kind: dataset
+    released: "2026-07"
+    venue: "Hugging Face"
+    year: 2026
+    status: open
+    url: https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset
+    data: https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset
+    scale: "Ten public LeRobot v2 episodes totaling about 2.37 GB with synchronized left/right egocentric video, high-frequency hand and head pose, and task/episode metadata"
+    modalities: [egocentric-video, stereo-video, hand-pose, head-pose, natural-language]
+    tasks: [robot-learning, imitation-learning, hand-object-interaction, sensor-fusion]
+    created_by: "Digital Divide Data Cambodia"
+    released_by: "DDD-Cambodia on Hugging Face"
+    license: cc-by-4.0
+    license_url: https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset/blob/main/README.md
+    verified_at: "2026-07-30"
+    citation_key: ddd_egocentric_sample_2026
+
+  - name: Showway Egocentric Origami Series
+    kind: collection
+    released: "2026-07"
+    venue: "Hugging Face"
+    year: 2026
+    status: open
+    url: https://huggingface.co/datasets/showway-ego/egocentric-origami-001
+    data: https://huggingface.co/showway-ego
+    scale: "Three public LeRobot v3 repositories with nine neck-mounted iPhone ultra-wide origami episodes, HaMeR-derived 3D hand joints, video, and human-reviewed narration"
+    modalities: [egocentric-video, hand-pose, natural-language]
+    tasks: [hand-object-interaction, procedure-understanding, imitation-learning, robot-learning]
+    created_by: "Showway Ego"
+    released_by: "showway-ego on Hugging Face"
+    license: apache-2.0
+    license_url: https://huggingface.co/datasets/showway-ego/egocentric-origami-001/blob/main/README.md
+    verified_at: "2026-07-30"
+    citation_key: showway_origami_2026
+
+  - name: EGXO Household Egocentric Video Evaluation
+    kind: dataset
+    released: "2026-07"
+    venue: "Hugging Face"
+    year: 2026
+    status: request
+    url: https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation
+    data: https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation
+    scale: "71 household-task videos totaling exactly 10 hours and about 43.4 GiB; six preview clips and task metadata are publicly visible while the complete media package requires a commercial data license"
+    modalities: [egocentric-video, natural-language, metadata]
+    tasks: [household-activity, procedure-understanding, robot-learning, hand-object-interaction]
+    created_by: "EGXO Data"
+    released_by: "egxodata on Hugging Face"
+    access: "public previews; complete media by commercial-license request"
+    license: other
+    license_url: https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation/blob/main/README.md
+    verified_at: "2026-07-30"
+    citation_key: egxo_household_2026
+
+  - name: Egocentric Hand Benchmark Annotations
+    kind: benchmark
+    released: "2026-07"
+    venue: "Hugging Face"
+    year: 2026
+    status: partial
+    url: https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark
+    data: https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark
+    derived_from: "EgoDaily and HOT3D"
+    scale: "100,427 public annotation rows: 95,002 EgoDaily hand boxes and 5,425 HOT3D virtual hand-crop camera records, distributed without the source RGB"
+    modalities: [hand-bounding-boxes, camera-pose, annotations]
+    tasks: [hand-detection, hand-tracking, hand-pose-estimation, benchmark]
+    created_by: "MacroData"
+    released_by: "macrodata on Hugging Face"
+    license: other
+    license_url: https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark/blob/main/README.md
+    verified_at: "2026-07-30"
+    release_note: "Annotations are public, but source imagery is not redistributed and remains subject to EgoDaily and HOT3D access and license terms."
+    citation_key: egocentric_hand_benchmark_annotations_2026
+
+  - name: ChildLens
+    kind: dataset
+    released: "2026-04"
+    venue: "Behavior Research Methods 2026"
+    year: 2026
+    status: request
+    url: https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/
+    project: https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/
+    paper: https://doi.org/10.3758/s13428-026-02982-6
+    code: https://github.com/neleSuffo/ChildLens
+    data: https://doi.org/10.17617/4.fe
+    scale: "109 hours of vest-mounted 140-degree egocentric video and audio from 62 children aged 3 to 5 in their homes, with five location classes and 14 exhaustively annotated activity classes"
+    modalities: [egocentric-video, audio, natural-language, annotations]
+    tasks: [child-development, activity-recognition, temporal-localization, voice-type-classification]
+    created_by: "Nele-Pauline Suffo, Pierre-Etienne Martin, Anas Suffo, Daniel Haun, and Manuel Bohn"
+    access: "researcher request and privacy review through the Max Planck Institute"
+    license: other
+    license_url: https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/
+    verified_at: "2026-07-30"
+    release_note: "The version of record and benchmark code are public. The child home recordings are available for research through DOI 10.17617/4.fe after a reviewed access request."
+    citation_key: childlens_2026
+
+  - name: HuMI
+    kind: dataset
+    released: "2026-02"
+    venue: "arXiv"
+    year: 2026
+    status: open
+    url: https://humanoid-manipulation-interface.github.io/
+    project: https://humanoid-manipulation-interface.github.io/
+    paper: https://arxiv.org/abs/2602.06643
+    code: https://github.com/Richard-coder-Nai/HuMI
+    data: https://huggingface.co/collections/Richard-Nai/humi
+    scale: "Portable robot-free whole-body demonstration interface and seven-dataset Hugging Face collection spanning five kneeling, squatting, tossing, walking, and bimanual tasks; reports 3x collection efficiency and 70% unseen-environment success"
+    modalities: [egocentric-video, wrist-video, body-pose, hand-pose, robot-actions]
+    tasks: [humanoid-manipulation, whole-body-control, imitation-learning, human-to-robot-transfer]
+    created_by: "Ruiqian Nai, Boyuan Zheng, Junming Zhao, Haodong Zhu, Sicong Dai, Zunhao Chen, Yihang Hu, Yingdong Hu, Tong Zhang, Chuan Wen, and Yang Gao"
+    license: "MIT code; CC-BY-4.0 datasets"
+    license_url: https://github.com/Richard-coder-Nai/HuMI/blob/main/LICENSE
+    verified_at: "2026-07-30"
+    release_note: "The MIT implementation and seven public Hugging Face data repositories are live. Dataset cards declare CC-BY-4.0."
+    citation_key: humi_2026
+
+  - name: ContactFlow
+    kind: model
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    scope: adjacent
+    url: https://arxiv.org/abs/2607.26579
+    paper: https://arxiv.org/abs/2607.26579
+    scale: "Embodiment-agnostic video action conditioning through trajectories of 3D actor-object contact points, trained with human and robot interactions and evaluated on DROID and real tabletop tasks"
+    modalities: [human-video, robot-video, 3d-contact, generated-video]
+    tasks: [world-modeling, human-to-robot-transfer, contact-reasoning, robot-manipulation]
+    created_by: "Sami Azirar, Enrico Pallotta, Jan Nogga, Jurgen Gall, Sven Behnke, and Hermann Blum"
+    verified_at: "2026-07-30"
+    release_note: "The paper is public, but no project page, implementation, model weights, training package, or reusable license was linked."
+    scope_note: "Uses general human interaction and robot videos; human wearable or first-person capture is not required."
+    citation_key: contactflow_2026
+
+  - name: Robot-Factored World Models
+    kind: model
+    released: "2026-07"
+    venue: "arXiv"
+    year: 2026
+    status: watch
+    scope: adjacent
+    url: https://bjkim95.github.io/rofacto/
+    project: https://bjkim95.github.io/rofacto/
+    paper: https://arxiv.org/abs/2607.22535
+    code: https://github.com/bjkim95/rofacto
+    scale: "Action-conditioned world model that factors robot control and appearance into nominal trajectories and rendered robot geometry, evaluated on DROID and egocentric RoboCasa-GR1 with zero-shot embodiments and human-demo retargeting"
+    modalities: [robot-video, depth, robot-actions, generated-video]
+    tasks: [world-modeling, robot-manipulation, cross-embodiment-transfer, video-generation]
+    created_by: "Byungjun Kim, Taeksoo Kim, Hyunsoo Cha, and Hanbyul Joo"
+    verified_at: "2026-07-30"
+    release_note: "The project and repository are public, but the repository still says code coming soon and declares no license."
+    scope_note: "Robot-camera world model with an egocentric humanoid evaluation, not a human wearable-capture resource."
+    citation_key: robot_factored_world_models_2026
+
   # --- Full live scan additions (2026-07-20): arXiv, project, code, and Hugging Face sweep ---
 
   - name: EgoExoMoCap
@@ -6958,17 +7292,23 @@ resources:
   - name: EgoMemReason
     kind: benchmark
     released: "2026-05"
-    venue: "arXiv"
+    venue: "COLM 2026"
     year: 2026
-    status: watch
-    url: https://arxiv.org/abs/2605.09874
+    status: open
+    url: https://huggingface.co/datasets/Ted412/EgoMemReason
+    project: https://egomemreason.github.io/
     paper: https://arxiv.org/abs/2605.09874
-    derived_from: week-long egocentric video
-    scale: "500 questions across entity, event, and behavior memory; average 25.9 hours of memory backtracking"
+    code: https://github.com/Ziyang412/EgoMemReason
+    data: https://huggingface.co/datasets/Ted412/EgoMemReason
+    leaderboard: https://huggingface.co/spaces/Ted412/EgoMemReason
+    derived_from: EgoLife
+    scale: "500 public multiple-choice questions over week-long EgoLife video across entity, event, and behavior memory; average 5.1 evidence segments and 25.9 hours of memory backtracking"
     tasks: [long-horizon-memory, entity-memory, event-memory, behavior-memory, egocentric-video-reasoning]
     created_by: Ziyang Wang, Yue Zhang, Shoubin Yu, Ce Zhang, Zengqi Zhao, Jaehong Yoon, Hyunji Lee, Gedas Bertasius, Mohit Bansal
-    release_note: arXiv paper; verify public data/code release before benchmark use
-    verified_at: "2026-06-20"
+    license: cc-by-nc-4.0
+    license_url: https://huggingface.co/datasets/Ted412/EgoMemReason/blob/main/README.md
+    release_note: "Accepted at COLM 2026. Public annotations, evaluation code, and leaderboard are live; raw EgoLife frames remain under EgoLife's separate license. Version 1.1 reshuffled answer-option letters on 2026-07-13, so older downloads must be refreshed."
+    verified_at: "2026-07-30"
   - name: EgoClip
     kind: dataset
     released: "2022-06"
@@ -8868,15 +9208,20 @@ resources:
   - name: EgoBrain
     kind: dataset
     released: "2025-06"
-    venue: "arXiv"
+    venue: "ICLR 2026"
     year: 2025
-    status: watch
-    url: https://arxiv.org/abs/2506.01353
+    status: request
+    url: https://huggingface.co/datasets/ut-vision/EgoBrain
     paper: https://arxiv.org/abs/2506.01353
-    scale: "Synchronized EEG and egocentric video for human action understanding from minds and eyes"
+    data: https://huggingface.co/datasets/ut-vision/EgoBrain
+    scale: "Complete 1.6 TB release from 40 participants with synchronized 4K GoPro egocentric video, EEG, IMU, interval markers, and surveys for human action understanding"
+    modalities: [egocentric-video, eeg, imu, natural-language, annotations]
     tasks: [eeg, action-understanding, multimodal]
-    verified_at: "2026-06-20"
-    release_note: "Live source checked 2026-06-20; kept on watch until public artifacts, access terms, or reproducible release metadata are confirmed."
+    access: "manual Hugging Face approval with research, privacy, and non-redistribution terms"
+    license: cc-by-nc-4.0
+    license_url: https://huggingface.co/datasets/ut-vision/EgoBrain/blob/main/README.md
+    verified_at: "2026-07-30"
+    release_note: "Accepted at ICLR 2026. The complete 40-participant release was uploaded by 2026-07-05 and is available through a manually approved Hugging Face gate."
   - name: MM-Ego
     kind: model
     released: "2024-10"

data/taxonomy.yml

@@ -49,7 +49,7 @@ task_families:
       egocentric-pretraining, egocentric-representation, mllm, multimodal-fusion,
       state-space-models, transfer-learning, weak-supervision, child-view-learning,
       multitask-learning, parameter-efficient-tuning, data-augmentation, egocentric-vision,
-      synthetic-data]
+      synthetic-data, data-curation, human-alignment]
 
   video-language:
     label: Video-language and captioning
@@ -88,7 +88,7 @@ task_families:
       action-reasoning, future-prediction, inference-strategy, intent-understanding,
       procedural-reasoning, structured-reasoning, neuro-symbolic-reasoning, state-transition-generation, trajectory-conditioning,
       goal-inference, long-horizon-reasoning, prompt-learning, high-stakes-egocentric-understanding,
-      physical-world-understanding, self-awareness]
+      physical-world-understanding, self-awareness, body-awareness, safety-reasoning]
 
   action-and-procedure:
     label: Action and procedure understanding
@@ -106,7 +106,8 @@ task_families:
       mistake-attribution, surgical-understanding, task-progress, object-state-change,
       action-selection, retail-understanding, human-behavior-understanding, industrial-egocentric-video,
       manipulation-understanding, progress-estimation, failure-understanding,
-      industrial-activity, procedural-learning]
+      industrial-activity, procedural-learning, event-detection, household-activity,
+      urban-understanding]
 
   hand-object-interaction:
     label: Hand-object interaction and contact
@@ -116,7 +117,7 @@ task_families:
       two-hand-pose, two-hand-segmentation, hand-forecasting, grasping, active-object-detection,
       active-object-segmentation, human-object-human-interaction, affordance, hoi, h2o,
       articulation-perception, hand-tracking, hoi-detection, hand-reconstruction,
-      3d-hand-reconstruction]
+      3d-hand-reconstruction, hand-pose-estimation, contact-reasoning]
 
   pose-and-body:
     label: Pose, body, and motion
@@ -147,13 +148,14 @@ task_families:
       digital-twin-evaluation, depth, egocentric-depth, reconstruction, egopat3d,
       3d-dialogue, 3d-scene-understanding, 3d-understanding, dynamic-scenes,
       view-synthesis, 3d-object-detection, surface-regression, articulated-objects,
-      semantic-mapping, 3d-spatial-reasoning]
+      semantic-mapping, 3d-spatial-reasoning, depth-estimation, camera-tracking]
 
   generation-and-world-models:
     label: Generation and world models
     aliases: [video-generation, world-modeling, action-conditioned-generation,
       egocentric-simulation, simulation, 3d-scene-generation, text-to-3d,
-      view-consistency, data-generation, world-action-models]
+      view-consistency, data-generation, world-action-models, world-action-model,
+      video-editing]
 
   grounding-localization:
     label: Grounding and localization
@@ -173,13 +175,16 @@ task_families:
       latent-action-learning, reinforcement-learning, contact-rich-manipulation, retargeting,
       digital-teleoperation, compositional-generalization, whole-body-control,
       human-robot-interaction, humanoid-robotics, multimodal-data-collection,
-      action-chunking, exploration, robot-control]
+      action-chunking, exploration, robot-control, failure-recovery,
+      human-to-robot-transfer, humanoid-manipulation, human-robot-collaboration,
+      vision-language-action]
 
   audio-and-social:
     label: Audio, speech, and social interaction
     aliases: [audio-visual, audio-visual-reasoning, sound-understanding, audio-event-recognition,
       audio-events, audio-triggered-capture, social, social-reasoning, first-person-interaction-recognition,
-      energy-efficient-smart-glasses, child-caregiver-interaction, multimodal-conversation]
+      energy-efficient-smart-glasses, child-caregiver-interaction, multimodal-conversation,
+      voice-type-classification, engagement-prediction]
 
   assistance-and-agents:
     label: Assistance and interactive agents
@@ -191,7 +196,9 @@ task_families:
       healthcare-assistance, procedural-assistance, proactive-assistance, real-time-assistance,
       remote-collaboration, situated-assistance, nutrition-estimation, medical-assistance,
       privacy, cognitive-state-aware-assistance, instruction-generation, health-ai,
-      wearable-assistants, visual-assistance, accessibility, assistive-robotics]
+      wearable-assistants, visual-assistance, accessibility, assistive-robotics,
+      context-aware-assistance, creativity-support, human-computer-interaction,
+      wearable-ai]
 
   ar-sensing-navigation:
     label: AR, wearable sensing, and navigation
@@ -201,12 +208,13 @@ task_families:
       360-video, mps, vrs-loading, driving, ar-wearables, avatar-rendering,
       edge-ai, egocentric-human-capture, gaze-analysis, on-device-perception,
       prototyping, relighting, visual-attention-prediction, affect-recognition,
-      personality-recognition]
+      personality-recognition, gaze-estimation, slam]
 
   skills-and-quality:
     label: Skill, proficiency, and quality
     aliases: [skill-assessment, action-quality, proficiency, skilled-activity,
-      cultural-heritage, esports-perception, motor-impairment-assessment]
+      cultural-heritage, esports-perception, motor-impairment-assessment,
+      child-development]
 
   evaluation-and-tooling:
     label: Evaluation, benchmarks, and tooling
@@ -218,7 +226,7 @@ task_families:
       streaming-video-understanding, zero-shot, multimodal-generalization, survey,
       data-conversion, data-selection, data-visualization, inference-runtime,
       action-evaluation, robot-deployment, test-time-scaling, backdoor-defense,
-      edge-inference, policy-stability, systems-optimization]
+      edge-inference, policy-stability, systems-optimization, streaming-video]
 
 # --- modality families ------------------------------------------------------
 modality_families:
@@ -235,7 +243,7 @@ modality_families:
       human-view-video, long-video, streaming-video, wrist-camera, lifelogging-video,
       synthetic-video, monocular-video, egocentric-observations, video-priors,
       body-worn-camera, latent-video, bimanual-video, images, uav-video,
-      vehicle-camera-video]
+      vehicle-camera-video, human-video, image, robot-video, wrist-video]
 
   depth:
     label: Depth and RGB-D
@@ -261,14 +269,15 @@ modality_families:
     aliases: [pose, 2d-pose, 3d-pose, 3d-hand-pose, 3d-human-pose, hand-pose, body-pose,
       human-pose, camera-pose, camera-poses, object-pose, full-body-mocap, hand-mocap,
       mocap, skeleton, keypoint-visibility, hand-trajectories, object-trajectories, 6dof, 3d-human-motion,
-      hand-skeleton, humanoid-motion, body-tracking]
+      hand-skeleton, humanoid-motion, body-tracking, gripper-pose]
 
   hand-object-geometry:
     label: Hand-object geometry and contact
     aliases: [hand, hands, contact, hand-masks, object-masks, object-boxes, hand-object-contact-masks,
       object-meshes, hand-meshes, hand-mesh, mesh, articulated-objects, 3d-objects, object-motion,
       tactile, pressure, force, glove-sensors, hand-object-contact,
-      hand-object-interaction, hand-object-motion, object-crops, objects]
+      hand-object-interaction, hand-object-motion, object-crops, objects,
+      3d-contact, hand-bounding-boxes]
 
   scene-3d:
     label: 3D scene and reconstruction
@@ -300,4 +309,4 @@ modality_families:
       logs, metadata, object-segmentation, temporal-localization, evaluation-logs,
       sensor-sidecars, semantic-masks, vr, dense-rewards, embodied-observations,
       latent-features, offline-demonstrations, synthetic-failures, visual-tokens,
-      visual-triggers]
+      visual-triggers, ar-headset, eeg, embodied-actions]

feed.xml

@@ -4,7 +4,7 @@
   <id>https://chaoyue0307.github.io/awesome-egocentric-atlas/feed.xml</id>
   <link href="https://chaoyue0307.github.io/awesome-egocentric-atlas/feed.xml" rel="self"/>
   <link href="https://chaoyue0307.github.io/awesome-egocentric-atlas/"/>
-  <updated>2026-07-20T00:00:00Z</updated>
+  <updated>2026-07-30T00:00:00Z</updated>
   <subtitle>Recently added egocentric AI resources, newest first.</subtitle>
 <entry>
   <title>yyyyywv/egocentric</title>

index.html

@@ -75,7 +75,7 @@
         "AR/VR",
         "hand-object interaction"
       ],
-      "dateModified": "2026-07-20",
+      "dateModified": "2026-07-30",
       "creator": {
         "@type": "Person",
         "name": "He Chaoyue"
@@ -87,12 +87,12 @@
         {
           "@type": "PropertyValue",
           "name": "Egocentric resources",
-          "value": 793
+          "value": 808
         },
         {
           "@type": "PropertyValue",
           "name": "Adjacent resources",
-          "value": 147
+          "value": 150
         }
       ]
     },
@@ -102,7 +102,7 @@
       "name": "Awesome Egocentric Atlas catalog export",
       "description": "Machine-readable catalog of the resources curated by Awesome Egocentric Atlas.",
       "url": "https://huggingface.co/datasets/cy0307/awesome-egocentric-atlas",
-      "dateModified": "2026-07-20",
+      "dateModified": "2026-07-30",
       "license": "https://opensource.org/license/mit",
       "isAccessibleForFree": true,
       "distribution": [
@@ -169,23 +169,23 @@
           </div>
           <dl class="stat-strip" aria-label="Atlas summary">
             <div>
-              <dt data-stat="egocentric_resources">793</dt>
+              <dt data-stat="egocentric_resources">808</dt>
               <dd data-i18n="stat.resources">egocentric resources</dd>
             </div>
             <div>
-              <dt data-kind="dataset">202</dt>
+              <dt data-kind="dataset">208</dt>
               <dd data-i18n="stat.datasets">datasets</dd>
             </div>
             <div>
-              <dt data-kind="benchmark">134</dt>
+              <dt data-kind="benchmark">137</dt>
               <dd data-i18n="stat.benchmarks">benchmarks</dd>
             </div>
             <div>
-              <dt data-kind="model">412</dt>
+              <dt data-kind="model">415</dt>
               <dd data-i18n="stat.models">models</dd>
             </div>
             <div>
-              <dt data-kind="toolkit">40</dt>
+              <dt data-kind="toolkit">42</dt>
               <dd data-i18n="stat.toolkits">toolkits</dd>
             </div>
           </dl>
@@ -202,7 +202,7 @@
           </picture>
           <div class="media-caption">
             <span data-i18n="media.caption">Egocentric AI research resources</span>
-            <span data-updated>Updated 2026-07-20</span>
+            <span data-updated>Updated 2026-07-30</span>
           </div>
         </div>
       </section>

site-data.json

@@ -2,7 +2,7 @@
   "meta": {
     "title": "Awesome Egocentric Atlas",
     "description": "Awesome Egocentric Atlas is a catalog of egocentric AI resources for egocentric vision, embodied AI, robotics, VLA, world models, WMA, memory, AR/VR, and hand-object interaction.",
-    "last_major_audit": "2026-07-20",
+    "last_major_audit": "2026-07-30",
     "status_legend": {
       "open": "Public download, public annotations, public code, or application-based access is clearly documented.",
       "request": "Public project exists, but dataset access requires license, form, approval, or institutional agreement.",
@@ -15,24 +15,24 @@
     "huggingface_url": "https://huggingface.co/datasets/cy0307/awesome-egocentric-atlas"
   },
   "summary": {
-    "total_resources": 940,
-    "egocentric_resources": 793,
-    "adjacent_resources": 147,
+    "total_resources": 958,
+    "egocentric_resources": 808,
+    "adjacent_resources": 150,
     "kind_counts": {
-      "benchmark": 134,
+      "benchmark": 137,
       "challenge": 1,
-      "collection": 2,
-      "dataset": 202,
-      "model": 412,
+      "collection": 3,
+      "dataset": 208,
+      "model": 415,
       "survey": 2,
-      "toolkit": 40
+      "toolkit": 42
     },
     "status_counts": {
       "benchmark": 11,
-      "open": 192,
-      "partial": 25,
-      "request": 20,
-      "watch": 545
+      "open": 198,
+      "partial": 27,
+      "request": 23,
+      "watch": 549
     }
   },
   "lanes": [
@@ -45,7 +45,7 @@
         "video-language",
         "generation-and-world-models"
       ],
-      "count": 218
+      "count": 221
     },
     {
       "id": "procedure-action",
@@ -55,7 +55,7 @@
         "action-and-procedure",
         "skills-and-quality"
       ],
-      "count": 242
+      "count": 247
     },
     {
       "id": "hands-3d",
@@ -68,7 +68,7 @@
         "detection-segmentation",
         "three-d-and-scene"
       ],
-      "count": 347
+      "count": 353
     },
     {
       "id": "memory-reasoning",
@@ -80,7 +80,7 @@
         "reasoning-intent-planning",
         "grounding-localization"
       ],
-      "count": 255
+      "count": 259
     },
     {
       "id": "robotics-vla",
@@ -89,7 +89,7 @@
       "families": [
         "robotics-and-vla"
       ],
-      "count": 203
+      "count": 210
     },
     {
       "id": "ar-wearables",
@@ -100,7 +100,7 @@
         "audio-and-social",
         "assistance-and-agents"
       ],
-      "count": 249
+      "count": 256
     }
   ],
   "milestones": [
@@ -522,6 +522,573 @@
       "license_url": "https://huggingface.co/datasets/ropedia-ai/xperience-10m-sample",
       "verified_at": "2026-06-20"
     },
+    {
+      "name": "ReViV",
+      "kind": "model",
+      "released": "2026-07",
+      "venue": "ECCV 2026",
+      "year": 2026,
+      "status": "open",
+      "scope": "egocentric",
+      "url": "https://reviv4d.github.io/",
+      "paper": "https://arxiv.org/abs/2607.17790",
+      "code": "https://github.com/lvsean/reviv4d",
+      "scale": "Unified feed-forward monocular egocentric 4D reconstruction of RGB, camera trajectory, gaze, body, hands, and depth; evaluated on HoloAssist, HOT3D, ARCTIC, Aria Digital Twin, TACO, and pretrained on more than 600 hours",
+      "tasks": [
+        "4d-reconstruction",
+        "camera-tracking",
+        "egocentric-3d-pose",
+        "gaze-estimation",
+        "depth-estimation"
+      ],
+      "task_families": [
+        "three-d-and-scene",
+        "pose-and-body",
+        "ar-sensing-navigation"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "camera-pose",
+        "gaze",
+        "body-pose",
+        "hand-pose",
+        "depth"
+      ],
+      "license": "Apache-2.0 code; non-commercial checkpoint terms",
+      "license_url": "https://github.com/lvsean/reviv4d/blob/main/LICENSE",
+      "release_note": "The implementation and pretrained checkpoints are public. Code is Apache-2.0; checkpoint use follows the separate non-commercial terms linked by the repository.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "EgoRecovery",
+      "kind": "model",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "egocentric",
+      "url": "https://arxiv.org/abs/2607.19745",
+      "paper": "https://arxiv.org/abs/2607.19745",
+      "scale": "Co-training framework that aligns egocentric human failure-recovery demonstrations with a corrective-intent space and a small robot-data anchor; its collection protocol yields more than 10x as much valid recovery data per hour as robot teleoperation",
+      "tasks": [
+        "failure-recovery",
+        "robot-learning",
+        "imitation-learning",
+        "human-to-robot-transfer"
+      ],
+      "task_families": [
+        "robotics-and-vla"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "human-demonstrations",
+        "robot-actions"
+      ],
+      "release_note": "The paper is public, but no project page, code, human-recovery corpus, robot data, or reusable license was linked during this audit.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "Sidewalk Moments",
+      "kind": "dataset",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "egocentric",
+      "url": "https://arxiv.org/abs/2607.20903",
+      "paper": "https://arxiv.org/abs/2607.20903",
+      "scale": "61 first-person YouTube city-walk videos segmented into more than 50,000 ten-second clips with video, temporally averaged image, audio, and text representations for human-aligned urban-engagement analysis",
+      "tasks": [
+        "urban-understanding",
+        "human-alignment",
+        "multimodal-representation",
+        "engagement-prediction"
+      ],
+      "task_families": [
+        "action-and-procedure",
+        "foundation-and-representation",
+        "audio-and-social"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "audio",
+        "natural-language",
+        "image"
+      ],
+      "release_note": "The manuscript is under review at Scientific Reports. No public clip list, annotations, extracted features, code, or dataset license was linked.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "CRAFT Wearable Creative AI",
+      "kind": "toolkit",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "egocentric",
+      "url": "https://arxiv.org/abs/2607.21394",
+      "paper": "https://arxiv.org/abs/2607.21394",
+      "scale": "Context-aware smart-glasses creative-AI probe studied through nine writer interviews, co-design with 16 writers and researchers, and 24 real-world sessions with eight writers",
+      "tasks": [
+        "wearable-ai",
+        "context-aware-assistance",
+        "human-computer-interaction",
+        "creativity-support"
+      ],
+      "task_families": [
+        "assistance-and-agents"
+      ],
+      "modalities": [
+        "smart-glasses",
+        "egocentric-video",
+        "natural-language"
+      ],
+      "release_note": "The arXiv record reports conditional PACM IMWUT acceptance pending minor revisions. No reusable prototype, study package, code, or license was linked, so the venue remains arXiv until final publication is verifiable.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "SHARE User-Centric AR SLAM",
+      "kind": "toolkit",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "egocentric",
+      "url": "https://arxiv.org/abs/2607.23901",
+      "paper": "https://arxiv.org/abs/2607.23901",
+      "scale": "User-prioritized edge SLAM for commercial head-mounted AR and a ground robot in shared workspaces; reports 13.22 ms average AR latency, a 43.3% reduction, while maintaining sub-2-centimeter tracking",
+      "tasks": [
+        "ar-vr",
+        "slam",
+        "human-robot-collaboration",
+        "localization"
+      ],
+      "task_families": [
+        "ar-sensing-navigation",
+        "robotics-and-vla",
+        "grounding-localization"
+      ],
+      "modalities": [
+        "ar-headset",
+        "egocentric-video",
+        "robot-video",
+        "camera-pose"
+      ],
+      "release_note": "The paper and user study are public, but no implementation, system traces, study data, or reusable license was linked.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "EgoPlay",
+      "kind": "model",
+      "released": "2026-07",
+      "venue": "SIGGRAPH Asia 2026",
+      "year": 2026,
+      "status": "partial",
+      "scope": "egocentric",
+      "url": "https://egoplay2026.github.io/egoplay/",
+      "paper": "https://arxiv.org/abs/2607.24560",
+      "scale": "Event-triggered egocentric video-to-video editing trained on 106K clip-prompt pairs, primarily from Ego4D, with positive, negative, and multi-event triggers plus event-aware evaluation",
+      "tasks": [
+        "video-editing",
+        "event-detection",
+        "video-generation",
+        "streaming-video"
+      ],
+      "task_families": [
+        "generation-and-world-models",
+        "action-and-procedure",
+        "evaluation-and-tooling"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "natural-language",
+        "generated-video"
+      ],
+      "release_note": "The accepted SIGGRAPH Asia 2026 paper and project demonstrations are public. The linked benchmark repository was unavailable during this audit, and no training data, model weights, code, or reusable license could be verified.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "Data Pyramid for Embodied Manipulation",
+      "kind": "survey",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "open",
+      "scope": "adjacent",
+      "url": "https://jasper-aaa.github.io/embodied-data-pyramid/",
+      "paper": "https://arxiv.org/abs/2607.24744",
+      "code": "https://github.com/worldbench/awesome-embodied-data-pyramid",
+      "scale": "Survey and living catalog organizing real-robot, UMI, human egocentric and ego-exo, simulation, and general video data into a five-level embodied-manipulation data pyramid",
+      "tasks": [
+        "survey",
+        "data-curation",
+        "robot-manipulation",
+        "embodied-ai"
+      ],
+      "task_families": [
+        "evaluation-and-tooling",
+        "foundation-and-representation",
+        "robotics-and-vla"
+      ],
+      "license": "apache-2.0",
+      "license_url": "https://github.com/worldbench/awesome-embodied-data-pyramid/blob/main/LICENSE",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "HiFi-UMI-2K",
+      "kind": "dataset",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "open",
+      "scope": "egocentric",
+      "url": "https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K",
+      "paper": "https://arxiv.org/abs/2607.25895",
+      "scale": "2,000 hours of public robot-free manipulation demonstrations from a high-fidelity UMI rig with head stereo-inertial SLAM, native inter-gripper pose, microsecond GPIO synchronization, and two roughly 200-degree cameras per hand; reports 3 mm local end-effector accuracy",
+      "tasks": [
+        "robot-learning",
+        "imitation-learning",
+        "vision-language-action",
+        "world-action-model",
+        "human-to-robot-transfer"
+      ],
+      "task_families": [
+        "robotics-and-vla",
+        "generation-and-world-models"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "stereo-video",
+        "wrist-video",
+        "camera-pose",
+        "gripper-pose",
+        "imu",
+        "robot-actions"
+      ],
+      "license": "cc-by-4.0",
+      "license_url": "https://huggingface.co/datasets/simple-world-lab/HiFi-UMI-2K/blob/main/README.md",
+      "release_note": "The ungated Hugging Face release is public under CC-BY-4.0. The paper distinguishes this 2,000-hour release from the larger internal corpus used in some experiments.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "EgoSafe-Bench",
+      "kind": "benchmark",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "egocentric",
+      "url": "https://arxiv.org/abs/2607.26518",
+      "paper": "https://arxiv.org/abs/2607.26518",
+      "scale": "12,000 safety-reasoning evaluation samples formed from 3,000 first-person mobile-captured clips and hierarchical QA chains spanning evidence anchoring, blind-spot deduction, intent inference, and causal consistency",
+      "tasks": [
+        "safety-reasoning",
+        "video-qa",
+        "causal-reasoning",
+        "benchmark"
+      ],
+      "task_families": [
+        "reasoning-intent-planning",
+        "question-answering",
+        "evaluation-and-tooling"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "video-qa",
+        "natural-language"
+      ],
+      "release_note": "The paper describes a new benchmark, but no public clips, annotations, evaluation code, project page, or license was linked.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "HumanCLAW-Bench",
+      "kind": "benchmark",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "egocentric",
+      "url": "https://human-claw.github.io/",
+      "paper": "https://arxiv.org/abs/2607.27180",
+      "code": "https://github.com/Human-CLAW/HumanCLAW",
+      "scale": "1,218 long-horizon egocentric find-navigate-interact episodes across 41 indoor scenes, evaluating nine VLMs through atomic full-body skill commands; the best reported success rate is 16.8%",
+      "tasks": [
+        "embodied-reasoning",
+        "navigation",
+        "interaction",
+        "body-awareness",
+        "benchmark"
+      ],
+      "task_families": [
+        "reasoning-intent-planning",
+        "ar-sensing-navigation",
+        "hand-object-interaction",
+        "evaluation-and-tooling"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "body-pose",
+        "natural-language",
+        "embodied-actions"
+      ],
+      "release_note": "The project and placeholder repository are public, but the repository says the code, benchmark, weights, and environment are still being prepared and declares no license.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "DDD Egocentric Stereo Manipulation Sample",
+      "kind": "dataset",
+      "released": "2026-07",
+      "venue": "Hugging Face",
+      "year": 2026,
+      "status": "open",
+      "scope": "egocentric",
+      "url": "https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset",
+      "scale": "Ten public LeRobot v2 episodes totaling about 2.37 GB with synchronized left/right egocentric video, high-frequency hand and head pose, and task/episode metadata",
+      "tasks": [
+        "robot-learning",
+        "imitation-learning",
+        "hand-object-interaction",
+        "sensor-fusion"
+      ],
+      "task_families": [
+        "robotics-and-vla",
+        "hand-object-interaction",
+        "ar-sensing-navigation"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "stereo-video",
+        "hand-pose",
+        "head-pose",
+        "natural-language"
+      ],
+      "license": "cc-by-4.0",
+      "license_url": "https://huggingface.co/datasets/DDD-Cambodia/ego-centric-sample-dataset/blob/main/README.md",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "Showway Egocentric Origami Series",
+      "kind": "collection",
+      "released": "2026-07",
+      "venue": "Hugging Face",
+      "year": 2026,
+      "status": "open",
+      "scope": "egocentric",
+      "url": "https://huggingface.co/datasets/showway-ego/egocentric-origami-001",
+      "scale": "Three public LeRobot v3 repositories with nine neck-mounted iPhone ultra-wide origami episodes, HaMeR-derived 3D hand joints, video, and human-reviewed narration",
+      "tasks": [
+        "hand-object-interaction",
+        "procedure-understanding",
+        "imitation-learning",
+        "robot-learning"
+      ],
+      "task_families": [
+        "hand-object-interaction",
+        "action-and-procedure",
+        "robotics-and-vla"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "hand-pose",
+        "natural-language"
+      ],
+      "license": "apache-2.0",
+      "license_url": "https://huggingface.co/datasets/showway-ego/egocentric-origami-001/blob/main/README.md",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "EGXO Household Egocentric Video Evaluation",
+      "kind": "dataset",
+      "released": "2026-07",
+      "venue": "Hugging Face",
+      "year": 2026,
+      "status": "request",
+      "scope": "egocentric",
+      "url": "https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation",
+      "scale": "71 household-task videos totaling exactly 10 hours and about 43.4 GiB; six preview clips and task metadata are publicly visible while the complete media package requires a commercial data license",
+      "tasks": [
+        "household-activity",
+        "procedure-understanding",
+        "robot-learning",
+        "hand-object-interaction"
+      ],
+      "task_families": [
+        "action-and-procedure",
+        "robotics-and-vla",
+        "hand-object-interaction"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "natural-language",
+        "metadata"
+      ],
+      "license": "other",
+      "license_url": "https://huggingface.co/datasets/egxodata/egxo-household-egocentric-video-evaluation/blob/main/README.md",
+      "access": "public previews; complete media by commercial-license request",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "Egocentric Hand Benchmark Annotations",
+      "kind": "benchmark",
+      "released": "2026-07",
+      "venue": "Hugging Face",
+      "year": 2026,
+      "status": "partial",
+      "scope": "egocentric",
+      "url": "https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark",
+      "derived_from": "EgoDaily and HOT3D",
+      "scale": "100,427 public annotation rows: 95,002 EgoDaily hand boxes and 5,425 HOT3D virtual hand-crop camera records, distributed without the source RGB",
+      "tasks": [
+        "hand-detection",
+        "hand-tracking",
+        "hand-pose-estimation",
+        "benchmark"
+      ],
+      "task_families": [
+        "hand-object-interaction",
+        "evaluation-and-tooling"
+      ],
+      "modalities": [
+        "hand-bounding-boxes",
+        "camera-pose",
+        "annotations"
+      ],
+      "license": "other",
+      "license_url": "https://huggingface.co/datasets/macrodata/egocentric-hand-benchmark/blob/main/README.md",
+      "release_note": "Annotations are public, but source imagery is not redistributed and remains subject to EgoDaily and HOT3D access and license terms.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "ChildLens",
+      "kind": "dataset",
+      "released": "2026-04",
+      "venue": "Behavior Research Methods 2026",
+      "year": 2026,
+      "status": "request",
+      "scope": "egocentric",
+      "url": "https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/",
+      "paper": "https://doi.org/10.3758/s13428-026-02982-6",
+      "code": "https://github.com/neleSuffo/ChildLens",
+      "scale": "109 hours of vest-mounted 140-degree egocentric video and audio from 62 children aged 3 to 5 in their homes, with five location classes and 14 exhaustively annotated activity classes",
+      "tasks": [
+        "child-development",
+        "activity-recognition",
+        "temporal-localization",
+        "voice-type-classification"
+      ],
+      "task_families": [
+        "skills-and-quality",
+        "action-and-procedure",
+        "grounding-localization",
+        "audio-and-social"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "audio",
+        "natural-language",
+        "annotations"
+      ],
+      "license": "other",
+      "license_url": "https://www.eva.mpg.de/comparative-cultural-psychology/technical-development/childlens/",
+      "access": "researcher request and privacy review through the Max Planck Institute",
+      "release_note": "The version of record and benchmark code are public. The child home recordings are available for research through DOI 10.17617/4.fe after a reviewed access request.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "HuMI",
+      "kind": "dataset",
+      "released": "2026-02",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "open",
+      "scope": "egocentric",
+      "url": "https://humanoid-manipulation-interface.github.io/",
+      "paper": "https://arxiv.org/abs/2602.06643",
+      "code": "https://github.com/Richard-coder-Nai/HuMI",
+      "scale": "Portable robot-free whole-body demonstration interface and seven-dataset Hugging Face collection spanning five kneeling, squatting, tossing, walking, and bimanual tasks; reports 3x collection efficiency and 70% unseen-environment success",
+      "tasks": [
+        "humanoid-manipulation",
+        "whole-body-control",
+        "imitation-learning",
+        "human-to-robot-transfer"
+      ],
+      "task_families": [
+        "robotics-and-vla"
+      ],
+      "modalities": [
+        "egocentric-video",
+        "wrist-video",
+        "body-pose",
+        "hand-pose",
+        "robot-actions"
+      ],
+      "license": "MIT code; CC-BY-4.0 datasets",
+      "license_url": "https://github.com/Richard-coder-Nai/HuMI/blob/main/LICENSE",
+      "release_note": "The MIT implementation and seven public Hugging Face data repositories are live. Dataset cards declare CC-BY-4.0.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "ContactFlow",
+      "kind": "model",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "adjacent",
+      "url": "https://arxiv.org/abs/2607.26579",
+      "paper": "https://arxiv.org/abs/2607.26579",
+      "scale": "Embodiment-agnostic video action conditioning through trajectories of 3D actor-object contact points, trained with human and robot interactions and evaluated on DROID and real tabletop tasks",
+      "tasks": [
+        "world-modeling",
+        "human-to-robot-transfer",
+        "contact-reasoning",
+        "robot-manipulation"
+      ],
+      "task_families": [
+        "generation-and-world-models",
+        "robotics-and-vla",
+        "hand-object-interaction"
+      ],
+      "modalities": [
+        "human-video",
+        "robot-video",
+        "3d-contact",
+        "generated-video"
+      ],
+      "release_note": "The paper is public, but no project page, implementation, model weights, training package, or reusable license was linked.",
+      "verified_at": "2026-07-30"
+    },
+    {
+      "name": "Robot-Factored World Models",
+      "kind": "model",
+      "released": "2026-07",
+      "venue": "arXiv",
+      "year": 2026,
+      "status": "watch",
+      "scope": "adjacent",
+      "url": "https://bjkim95.github.io/rofacto/",
+      "paper": "https://arxiv.org/abs/2607.22535",
+      "code": "https://github.com/bjkim95/rofacto",
+      "scale": "Action-conditioned world model that factors robot control and appearance into nominal trajectories and rendered robot geometry, evaluated on DROID and egocentric RoboCasa-GR1 with zero-shot embodiments and human-demo retargeting",
+      "tasks": [
+        "world-modeling",
+        "robot-manipulation",
+        "cross-embodiment-transfer",
+        "video-generation"
+      ],
+      "task_families": [
+        "generation-and-world-models",
+        "robotics-and-vla"
+      ],
+      "modalities": [
+        "robot-video",
+        "depth",
+        "robot-actions",
+        "generated-video"
+      ],
+      "release_note": "The project and repository are public, but the repository still says code coming soon and declares no license.",
+      "verified_at": "2026-07-30"
+    },
     {
       "name": "EgoExoMoCap",
       "kind": "model",
@@ -13726,14 +14293,15 @@
       "name": "EgoMemReason",
       "kind": "benchmark",
       "released": "2026-05",
-      "venue": "arXiv",
+      "venue": "COLM 2026",
       "year": 2026,
-      "status": "watch",
+      "status": "open",
       "scope": "egocentric",
-      "url": "https://arxiv.org/abs/2605.09874",
+      "url": "https://huggingface.co/datasets/Ted412/EgoMemReason",
       "paper": "https://arxiv.org/abs/2605.09874",
-      "derived_from": "week-long egocentric video",
-      "scale": "500 questions across entity, event, and behavior memory; average 25.9 hours of memory backtracking",
+      "code": "https://github.com/Ziyang412/EgoMemReason",
+      "derived_from": "EgoLife",
+      "scale": "500 public multiple-choice questions over week-long EgoLife video across entity, event, and behavior memory; average 5.1 evidence segments and 25.9 hours of memory backtracking",
       "tasks": [
         "long-horizon-memory",
         "entity-memory",
@@ -13745,8 +14313,10 @@
         "memory-and-long-context",
         "reasoning-intent-planning"
       ],
-      "release_note": "arXiv paper; verify public data/code release before benchmark use",
-      "verified_at": "2026-06-20"
+      "license": "cc-by-nc-4.0",
+      "license_url": "https://huggingface.co/datasets/Ted412/EgoMemReason/blob/main/README.md",
+      "release_note": "Accepted at COLM 2026. Public annotations, evaluation code, and leaderboard are live; raw EgoLife frames remain under EgoLife's separate license. Version 1.1 reshuffled answer-option letters on 2026-07-13, so older downloads must be refreshed.",
+      "verified_at": "2026-07-30"
     },
     {
       "name": "EgoClip",
@@ -17537,13 +18107,13 @@
       "name": "EgoBrain",
       "kind": "dataset",
       "released": "2025-06",
-      "venue": "arXiv",
+      "venue": "ICLR 2026",
       "year": 2025,
-      "status": "watch",
+      "status": "request",
       "scope": "egocentric",
-      "url": "https://arxiv.org/abs/2506.01353",
+      "url": "https://huggingface.co/datasets/ut-vision/EgoBrain",
       "paper": "https://arxiv.org/abs/2506.01353",
-      "scale": "Synchronized EEG and egocentric video for human action understanding from minds and eyes",
+      "scale": "Complete 1.6 TB release from 40 participants with synchronized 4K GoPro egocentric video, EEG, IMU, interval markers, and surveys for human action understanding",
       "tasks": [
         "eeg",
         "action-understanding",
@@ -17554,8 +18124,18 @@
         "action-and-procedure",
         "foundation-and-representation"
       ],
-      "release_note": "Live source checked 2026-06-20; kept on watch until public artifacts, access terms, or reproducible release metadata are confirmed.",
-      "verified_at": "2026-06-20"
+      "modalities": [
+        "egocentric-video",
+        "eeg",
+        "imu",
+        "natural-language",
+        "annotations"
+      ],
+      "license": "cc-by-nc-4.0",
+      "license_url": "https://huggingface.co/datasets/ut-vision/EgoBrain/blob/main/README.md",
+      "access": "manual Hugging Face approval with research, privacy, and non-redistribution terms",
+      "release_note": "Accepted at ICLR 2026. The complete 40-participant release was uploaded by 2026-07-05 and is available through a manually approved Hugging Face gate.",
+      "verified_at": "2026-07-30"
     },
     {
       "name": "MM-Ego",

sitemap.xml

@@ -2,7 +2,7 @@
 <urlset xmlns="http://www.sitemaps.org/schemas/sitemap/0.9">
   <url>
     <loc>https://chaoyue0307.github.io/awesome-egocentric-atlas/</loc>
-    <lastmod>2026-07-20</lastmod>
+    <lastmod>2026-07-30</lastmod>
     <changefreq>daily</changefreq>
     <priority>1.0</priority>
   </url>