paper_id string | title string | authors list | ecva_url string | pdf_url string | supp_url string | doi string | arxiv_id string | arxiv_id_source string | abstract large_string |
|---|---|---|---|---|---|---|---|---|---|
3335_ECCV_2020_paper | DTVNet: Dynamic Time-lapse Video Generation via Single Still Image | [
"Jiangning Zhang",
"Chao Xu",
"Liang Liu",
"Mengmeng Wang",
"Xia Wu",
"Yong Liu",
"Yunliang Jiang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3335_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500290.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500290-supp.zip | 10.1007/978-3-030-58558-7_18 | null | null | This paper presents a novel end-to-end dynamic time-lapse video generation framework, named DTVNet, to generate diversified time-lapse videos from a single landscape image, which are conditioned on normalized motion vectors. The proposed DTVNet consists of two submodules: mph{Optical Flow Encoder} (OFE) and mph{Dynam... |
3365_ECCV_2020_paper | CLIFFNet for Monocular Depth Estimation with Hierarchical Embedding Loss | [
"Lijun Wang",
"Jianming Zhang",
"Yifan Wang",
"Huchuan Lu",
"Xiang Ruan"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3365_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500307.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500307-supp.zip | 10.1007/978-3-030-58558-7_19 | null | null | This paper proposes a hierarchical loss for monocular depth estimation, which measures the differences between the prediction and ground truth in hierarchical embedding spaces of depth maps. In order to find an appropriate embedding space, we design different architectures for hierarchical embedding generators (HEGs) a... |
3385_ECCV_2020_paper | Collaborative Video Object Segmentation by Foreground-Background Integration | [
"Zongxin Yang",
"Yunchao Wei",
"Yi Yang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3385_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500324.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500324-supp.zip | 10.1007/978-3-030-58558-7_20 | 2003.08333 | title_snapshot | This paper investigates the principles of embedding learning to tackle the challenging semi-supervised video object segmentation. Different from previous practices that only explore the embedding learning using pixels from foreground object (s), we consider background should be equally treated and thus propose Collabor... |
3456_ECCV_2020_paper | Adaptive Margin Diversity Regularizer for handling Data Imbalance in Zero-Shot SBIR | [
"Titir Dutta",
"Anurag Singh",
"Soma Biswas"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3456_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500341.pdf | null | 10.1007/978-3-030-58558-7_21 | null | null | Data from new categories are continuously being discovered, which has sparked significant amount of research in developing approaches which generalizes to previously unseen categories, i.e. zero-shot setting. Zero-shot sketch-based image retrieval~(ZS-SBIR) is one such problem in the context of cross-domain retrieval, ... |
3477_ECCV_2020_paper | ETH-XGaze: A Large Scale Dataset for Gaze Estimation under Extreme Head Pose and Gaze Variation | [
"Xucong Zhang",
"Seonwook Park",
"Thabo Beeler",
"Derek Bradley",
"Siyu Tang",
"Otmar Hilliges"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3477_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500358.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500358-supp.zip | 10.1007/978-3-030-58558-7_22 | 2007.15837 | title_snapshot | Gaze estimation is a fundamental task in many applications of computer vision, human computer interaction and robotics. Many state-of-the-art methods are trained and tested on custom datasets, making comparison across methods challenging. Furthermore, existing gaze estimation datasets have limited head pose and gaze va... |
3499_ECCV_2020_paper | Calibration-free Structure-from-Motion with Calibrated Radial Trifocal Tensors | [
"Viktor Larsson",
"Nicolas Zobernig",
"Kasim Taskin",
"Marc Pollefeys"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3499_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500375.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500375-supp.zip | 10.1007/978-3-030-58558-7_23 | null | null | In this paper we consider the problem of Structure-from-Motion from images with unknown intrinsic calibration. Instead of estimating the internal camera parameters through some self-calibration procedure, we propose to use a subset of the reprojection constraints that is invariant to radial displacement. This allows us... |
3594_ECCV_2020_paper | Occupancy Anticipation for Efficient Exploration and Navigation | [
"Santhosh K. Ramakrishnan",
"Ziad Al-Halah",
"Kristen Grauman"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3594_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500392.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500392-supp.zip | 10.1007/978-3-030-58558-7_24 | 2008.09285 | title_snapshot | State-of-the-art navigation methods leverage a spatial memory to generalize to new environments, but their occupancy maps are limited to capturing the geometric structures directly observed by the agent. We propose occupancy anticipation, where the agent uses its egocentric RGB-D observations to infer the occupancy sta... |
3601_ECCV_2020_paper | Unified Image and Video Saliency Modeling | [
"Richard Droste",
"Jianbo Jiao",
"J. Alison Noble"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3601_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500409.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500409-supp.zip | 10.1007/978-3-030-58558-7_25 | 2003.05477 | title_snapshot | Visual saliency modeling for images and videos is treated as two independent tasks in recent computer vision literature. While image saliency modeling is a well-studied problem and progress on benchmarks like SALICON and MIT300 is slowing, video saliency models have shown rapid gains on the recent DHF1K benchmark. Here... |
3604_ECCV_2020_paper | TAO: A Large-Scale Benchmark for Tracking Any Object | [
"Achal Dave",
"Tarasha Khurana",
"Pavel Tokmakov",
"Cordelia Schmid",
"Deva Ramanan"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3604_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500426.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500426-supp.pdf | 10.1007/978-3-030-58558-7_26 | 2005.10356 | title_snapshot | For many years, multi-object tracking benchmarks have focused on a handful of categories. Motivated primarily by surveillance and self-driving applications, these datasets provide tracks for people, vehicles, and animals, ignoring the vast majority of objects in the world. By contrast, in the related field of object de... |
3657_ECCV_2020_paper | A Generalization of Otsu’s Method and Minimum Error Thresholding | [
"Jonathan T. Barron"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3657_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500443.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500443-supp.pdf | 10.1007/978-3-030-58558-7_27 | 2007.07350 | title_snapshot | We present Generalized Histogram Thresholding (GHT), a simple, fast, and effective technique for histogram-based image thresholding. GHT works by performing approximate maximum a posteriori estimation of a mixture of Gaussians with appropriate priors. We demonstrate that GHT subsumes three classic thresholding techniqu... |
3663_ECCV_2020_paper | A Cordial Sync: Going Beyond Marginal Policies for Multi-Agent Embodied Tasks | [
"Unnat Jain",
"Luca Weihs",
"Eric Kolve",
"Ali Farhadi",
"Svetlana Lazebnik",
"Aniruddha Kembhavi",
"Alexander Schwing"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3663_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500460.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500460-supp.pdf | 10.1007/978-3-030-58558-7_28 | 2007.04979 | title_snapshot | Autonomous agents must learn to collaborate. It is not scalable to develop a new centralized agent every time a task’s difficulty outpaces a single agent’s abilities. While multi-agent collaboration research has flourished in gridworld-like environments, relatively little work has considered visually rich domains. Addr... |
3665_ECCV_2020_paper | Big Transfer (BiT): General Visual Representation Learning | [
"Alexander Kolesnikov",
"Lucas Beyer",
"Xiaohua Zhai",
"Joan Puigcerver",
"Jessica Yung",
"Sylvain Gelly",
"Neil Houlsby"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3665_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500477.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500477-supp.pdf | 10.1007/978-3-030-58558-7_29 | 1912.11370 | title_snapshot | Transfer of pre-trained representations improves sample efficiency and simplifies hyperparameter tuning when training deep neural networks for vision. We revisit the paradigm of pre-training on large supervised datasets and fine-tuning the model on a target task. We scale up pre-training, and propose a simple recipe th... |
3684_ECCV_2020_paper | VisualCOMET: Reasoning about the Dynamic Context of a Still Image | [
"Jae Sung Park",
"Chandra Bhagavatula",
"Roozbeh Mottaghi",
"Ali Farhadi",
"Yejin Choi"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3684_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500494.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500494-supp.pdf | 10.1007/978-3-030-58558-7_30 | 2004.10796 | title_snapshot | Even from a single frame of a still image, people can reason about the dynamic story of the image before, after, and beyond the frame. For example, given an image of a man struggling to stay afloat in water, we can reason that the man fell into the water sometime in the past, the intent of that man at the moment is to ... |
3831_ECCV_2020_paper | Few-shot Action Recognition with Permutation-invariant Attention | [
"Hongguang Zhang",
"Li Zhang",
"Xiaojuan Qi",
"Hongdong Li",
"Philip H. S. Torr",
"Piotr Koniusz"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3831_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500511.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500511-supp.pdf | 10.1007/978-3-030-58558-7_31 | 2001.03905 | title_snapshot | Many few-shot learning models focus on recognising images. In contrast, we tackle a challenging task of few-shot action recognition from videos. We build on a C3D encoder for spatio-temporal video blocks to capture short-range action patterns. Such encoded blocks are aggregated by permutation-invariant pooling to make ... |
3913_ECCV_2020_paper | Character Grounding and Re-Identification in Story of Videos and Text Descriptions | [
"Youngjae Yu",
"Jongseok Kim",
"Heeseung Yun",
"Jiwan Chung",
"Gunhee Kim"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3913_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500528.pdf | null | 10.1007/978-3-030-58558-7_32 | null | null | We address character grounding and re-identification in multiple story-based videos like movies and associated text descriptions. In order to solve these related tasks in a mutually rewarding way, we propose a model named Character in Story Identification Network (CiSIN). Our method builds two semantically informative ... |
3977_ECCV_2020_paper | AABO: Adaptive Anchor Box Optimization for Object Detection via Bayesian Sub-sampling | [
"Wenshuo Ma",
"Tingzhong Tian",
"Hang Xu",
"Yimin Huang",
"Zhenguo Li"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3977_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500545.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500545-supp.pdf | 10.1007/978-3-030-58558-7_33 | 2007.09336 | title_snapshot | Most state-of-the-art object detection systems follow an anchor-based diagram. Anchor boxes are densely proposed over the images and the network is trained to predict the boxes position offset as well as the classification confidence. Existing systems pre-define anchor box shapes and sizes and ad-hoc heuristic adjustme... |
3984_ECCV_2020_paper | Learning Visual Context by Comparison | [
"Minchul Kim",
"Jongchan Park",
"Seil Na",
"Chang Min Park",
"Donggeun Yoo"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3984_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500562.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500562-supp.pdf | 10.1007/978-3-030-58558-7_34 | 2007.07506 | title_snapshot | Finding diseases from an X-ray image is an important yet highly challenging task. Current methods for solving this task exploit various characteristics of the chest X-ray image, but one of the most important characteristics is still missing: the necessity of comparison between related regions in an image. In this paper... |
3994_ECCV_2020_paper | Large Scale Holistic Video Understanding | [
"Ali Diba",
"Mohsen Fayyaz",
"Vivek Sharma",
"Manohar Paluri",
"Jürgen Gall",
"Rainer Stiefelhagen",
"Luc Van Gool"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3994_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500579.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500579-supp.pdf | 10.1007/978-3-030-58558-7_35 | 1904.11451 | title_snapshot | Video recognition has been advanced in recent years by benchmarks with rich annotations. However, research is still mainly limited to human action or sports recognition - focusing on a highly specific video understanding task and thus leaving a significant gap towards describing the overall content of a video. We fill ... |
3995_ECCV_2020_paper | Indirect Local Attacks for Context-aware Semantic Segmentation Networks | [
"Krishna Kanth Nakka",
"Mathieu Salzmann"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/3995_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500596.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500596-supp.pdf | 10.1007/978-3-030-58558-7_36 | 1911.13038 | title_snapshot | Recently, deep networks have achieved impressive semantic segmentation performance, in particular thanks to their use of larger contextual information. In this paper, we show that the resulting networks are sensitive not only to global adversarial attacks, where perturbations affect the entire input image, but also to ... |
4294_ECCV_2020_paper | Predicting Visual Overlap of Images Through Interpretable Non-Metric Box Embeddings | [
"Anita Rau",
"Guillermo Garcia-Hernando",
"Danail Stoyanov",
"Gabriel J. Brostow",
"Daniyar Turmukhambetov"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4294_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500613.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500613-supp.zip | 10.1007/978-3-030-58558-7_37 | 2008.05785 | title_snapshot | To what extent are two images picturing the same 3D surfaces? Even when this is a known scene, the answer typically requires an expensive search across scale space, with matching and geometric verification of large sets of local features. This expense is further multiplied when a query image is evaluated against a gall... |
4296_ECCV_2020_paper | Connecting Vision and Language with Localized Narratives | [
"Jordi Pont-Tuset",
"Jasper Uijlings",
"Soravit Changpinyo",
"Radu Soricut",
"Vittorio Ferrari"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4296_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500630.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500630-supp.pdf | 10.1007/978-3-030-58558-7_38 | 1912.03098 | title_snapshot | We propose Localized Narratives, a new form of multimodal image annotations connecting vision and language. We ask annotators to describe an image with their voice while simultaneously hovering their mouse over the region they are describing. Since the voice and the mouse pointer are synchronized, we can localize every... |
4383_ECCV_2020_paper | Adversarial T-shirt! Evading Person Detectors in A Physical World | [
"Kaidi Xu",
"Gaoyuan Zhang",
"Sijia Liu",
"Quanfu Fan",
"Mengshu Sun",
"Hongge Chen",
"Pin-Yu Chen",
"Yanzhi Wang",
"Xue Lin"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4383_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500647.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500647-supp.pdf | 10.1007/978-3-030-58558-7_39 | 1910.11099 | title_snapshot | It is known that deep neural networks (DNNs) are vulnerable to adversarial attacks. The so-called physical adversarial examples deceive DNN-based decision makers by attaching adversarial patches to real objects. However, most of the existing works on physical adversarial attacks focus on static objects such as glass fr... |
4404_ECCV_2020_paper | Bounding-box Channels for Visual Relationship Detection | [
"Sho Inayoshi",
"Keita Otani",
"Antonio Tejero-de-Pablos",
"Tatsuya Harada"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4404_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500664.pdf | null | 10.1007/978-3-030-58558-7_40 | null | null | Recognizing the relationship between multiple objects in an image is essential for a deeper understanding of the meaning of the image. However, current visual recognition methods are still far from reaching human-level accuracy. Recent approaches have tackled this task by combining image features with semantic and spat... |
4407_ECCV_2020_paper | Minimal Rolling Shutter Absolute Pose with Unknown Focal Length and Radial Distortion | [
"Zuzana Kukelova",
"Cenek Albl",
"Akihiro Sugimoto",
"Konrad Schindler",
"Tomas Pajdla"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4407_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500681.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500681-supp.pdf | 10.1007/978-3-030-58558-7_41 | 2004.14052 | title_snapshot | The internal geometry of most modern consumer cameras is not adequately described by the perspective projection. Almost all cameras exhibit some radial lens distortion and are equipped with electronic rolling shutter that induces distortions when the camera moves during the image capture. When focal length has not been... |
4442_ECCV_2020_paper | SRFlow: Learning the Super-Resolution Space with Normalizing Flow | [
"Andreas Lugmayr",
"Martin Danelljan",
"Luc Van Gool",
"Radu Timofte"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4442_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500698.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500698-supp.pdf | 10.1007/978-3-030-58558-7_42 | 2006.14200 | title_snapshot | Super-resolution is an ill-posed problem, since it allows for multiple predictions for a given low-resolution image. This fundamental fact is largely ignored by state-of-the-art deep learning based approaches. These methods instead train a deterministic mapping using combinations of reconstruction and adversarial losse... |
4452_ECCV_2020_paper | DeepGMR: Learning Latent Gaussian Mixture Models for Registration | [
"Wentao Yuan",
"Benjamin Eckart",
"Kihwan Kim",
"Varun Jampani",
"Dieter Fox",
"Jan Kautz"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4452_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500715.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500715-supp.pdf | 10.1007/978-3-030-58558-7_43 | 2008.09088 | title_snapshot | Point cloud registration is a fundamental problem in 3D computer vision, graphics and robotics. For the last few decades, existing registration algorithms have struggled in situations with large transformations, noise, and time constraints. In this paper, we introduce Deep Gaussian Mixture Registration (DeepGMR), the f... |
4458_ECCV_2020_paper | Active Perception using Light Curtains for Autonomous Driving | [
"Siddharth Ancha",
"Yaadhav Raaj",
"Peiyun Hu",
"Srinivasa G. Narasimhan",
"David Held"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4458_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500732.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500732-supp.zip | 10.1007/978-3-030-58558-7_44 | 2008.02191 | title_snapshot | Most real-world 3D sensors such as LiDARs are passive, meaning that they sense the entire environment, while being decoupled from the recognition system that processes the sensor data. In this work, we propose a method for 3D object recognition using light curtains, a resource-efficient active sensor that measures dept... |
4521_ECCV_2020_paper | Invertible Neural BRDF for Object Inverse Rendering | [
"Zhe Chen",
"Shohei Nobuhara",
"Ko Nishino"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4521_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500749.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500749-supp.pdf | 10.1007/978-3-030-58558-7_45 | 2008.04030 | title_snapshot | We introduce a novel neural network-based BRDF model and a Bayesian framework for object inverse rendering, i.e., joint estimation of reflectance and natural illumination from a single image of an object of known geometry. The BRDF is expressed with an invertible neural network, namely, normalizing flow, which provides... |
4545_ECCV_2020_paper | Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network | [
"Wenfeng Luo",
"Meng Yang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4545_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500766.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123500766-supp.pdf | 10.1007/978-3-030-58558-7_46 | null | null | While existing works have explored a variety of techniques to push the envelop of weakly-supervised semantic segmentation, there is still a significant gap compared to the supervised methods. In real-world application, besides massive amount of weakly-supervised data there are usually a few available pixel-level annota... |
4571_ECCV_2020_paper | Practical Deep Raw Image Denoising on Mobile Devices | [
"Yuzhi Wang",
"Haibin Huang",
"Qin Xu",
"Jiaming Liu",
"Yiqun Liu",
"Jue Wang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4571_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510001.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510001-supp.pdf | 10.1007/978-3-030-58539-6_1 | 2010.06935 | title_snapshot | Deep learning-based image denoising approaches have been extensively studied in recent years, prevailing in many public benchmark datasets. However, the stat-of-the-art networks are computationally too expensive to be directly applied on mobile devices. In this work, we propose a light-weight, efficient neural network-... |
4577_ECCV_2020_paper | SoundSpaces: Audio-Visual Navigation in 3D Environments | [
"Changan Chen",
"Unnat Jain",
"Carl Schissler",
"Sebastia Vicenc Amengual Gari",
"Ziad Al-Halah",
"Vamsi Krishna Ithapu",
"Philip Robinson",
"and Kristen Grauman"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4577_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510018.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510018-supp.pdf | 10.1007/978-3-030-58539-6_2 | 1912.11474 | title_snapshot | Moving around in the world is naturally a multi-sensory experience, but today's embodied agents are deaf - restricted to solely their visual perception of the environment. We introduce audio-visual navigation for complex, acoustically and visually realistic 3D environments. By both seeing and hearing, the agent must le... |
4602_ECCV_2020_paper | Two-Stream Consensus Network for Weakly-Supervised Temporal Action Localization | [
"Yuanhao Zhai",
"Le Wang",
"Wei Tang",
"Qilin Zhang",
"Junsong Yuan",
"Gang Hua"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4602_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510035.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510035-supp.pdf | 10.1007/978-3-030-58539-6_3 | 2010.11594 | title_snapshot | Weakly-supervised Temporal Action Localization (W-TAL) aims to classify and localize all action instances in an untrimmed video under only video-level supervision. However, without frame-level annotations, it is challenging for W-TAL methods to identify false positive action proposals and generate action proposals with... |
4677_ECCV_2020_paper | Erasing Appearance Preservation in Optimization-based Smoothing | [
"Lvmin Zhang",
"Chengze Li",
"Yi JI",
"Chunping Liu",
"Tien-tsin Wong"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4677_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510052.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510052-supp.zip | 10.1007/978-3-030-58539-6_4 | null | null | Optimization-based image smoothing is routinely formulated as the game between a smoothing energy and an appearance preservation energy. Achieving adequate smoothing is a fundamental goal of these image smoothing algorithms. We show that partially ""erasing"" the appearance preservation facilitate adequate image smooth... |
4727_ECCV_2020_paper | Counterfactual Vision-and-Language Navigation via Adversarial Path Sampler | [
"Tsu-Jui Fu",
"Xin Eric Wang",
"Matthew F. Peterson",
"Scott T. Grafton",
"Miguel P. Eckstein",
"William Yang Wang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4727_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510069.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510069-supp.pdf | 10.1007/978-3-030-58539-6_5 | 1911.07308 | title_judge | Vision-and-Language Navigation (VLN) is a task where agents must decide how to move through a 3D environment to reach a goal by grounding natural language instructions to the visual surroundings. One of the problems of the VLN task is data scarcity since it is difficult to collect enough navigation paths with human-ann... |
4749_ECCV_2020_paper | Guided Deep Decoder: Unsupervised Image Pair Fusion | [
"Tatsumi Uezato",
"Danfeng Hong",
"Naoto Yokoya",
"Wei He"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4749_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510086.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510086-supp.pdf | 10.1007/978-3-030-58539-6_6 | 2007.11766 | title_snapshot | The fusion of input and guidance images that have a tradeoff in their information (e.g., hyperspectral and RGB image fusion or pansharpening) can be interpreted as one general problem. However, previous studies applied a task-specific handcrafted prior and did not address the problems with a unified approach. To addres... |
4809_ECCV_2020_paper | Filter Style Transfer between Photos | [
"Jonghwa Yim",
"Jisung Yoo",
"Won-joon Do",
"Beomsu Kim",
"Jihwan Choe"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4809_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510103.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510103-supp.pdf | 10.1007/978-3-030-58539-6_7 | 2007.07925 | title_snapshot | Over the past few years, image-to-image style transfer has risen to the frontiers of neural image processing. While conventional methods were successful in various tasks such as color and texture transfer between images, none could effectively work with the custom filter effects that are applied by users through variou... |
4860_ECCV_2020_paper | JGR-P2O: Joint Graph Reasoning based Pixel-to-Offset Prediction Network for 3D Hand Pose Estimation from a Single Depth Image | [
"Linpu Fang",
"Xingyan Liu",
"Li Liu",
"Hang Xu",
"Wenxiong Kang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4860_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510120.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510120-supp.pdf | 10.1007/978-3-030-58539-6_8 | 2007.04646 | title_snapshot | State-of-the-art single depth image-based 3D hand pose estimation methods are based on dense predictions, including voxel-to-voxel predictions, point-to-point regression, and pixel-wise estimations. Despite the good performance, those methods have a few issues in nature, such as the poor trade-off between accuracy and ... |
4867_ECCV_2020_paper | Dynamic Group Convolution for Accelerating Convolutional Neural Networks | [
"Zhuo Su",
"Linpu Fang",
"Wenxiong Kang",
"Dewen Hu",
"Matti Pietikäinen",
"Li Liu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4867_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510137.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510137-supp.pdf | 10.1007/978-3-030-58539-6_9 | 2007.04242 | title_snapshot | Replacing normal convolutions with group convolutions can significantly increase the computational efficiency of modern deep convolutional networks, which has been widely adopted in compact network architecture designs. However, existing group convolutions undermine the original network structures by cutting off some c... |
4880_ECCV_2020_paper | RD-GAN: Few/Zero-Shot Chinese Character Style Transfer via Radical Decomposition and Rendering | [
"Yaoxiong Huang",
"Mengchao He",
"Lianwen Jin",
"Yongpan Wang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4880_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510154.pdf | null | 10.1007/978-3-030-58539-6_10 | null | null | Style transfer has attracted much interest owing to its various applications. Compared with English character or general artistic style transfer, Chinese character style transfer remains a challenge owing to the large size of the vocabulary(70224 characters in GB18010-2005) and the complexity of the structure. Recently... |
5021_ECCV_2020_paper | Object-Contextual Representations for Semantic Segmentation | [
"Yuhui Yuan",
"Xilin Chen",
"Jingdong Wang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5021_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510171.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510171-supp.pdf | 10.1007/978-3-030-58539-6_11 | 1909.11065 | title_judge | In this paper, we address the semantic segmentation problem with a focus on the context aggregation strategy. Our motivation is that the label of a pixel is the category of the object that the pixel belongs to. We present a simple yet effective approach, object-contextual representations, characterizing a pixel by expl... |
5116_ECCV_2020_paper | Efficient Spatio-Temporal Recurrent Neural Network for Video Deblurring | [
"Zhihang Zhong",
"Ye Gao",
"Yinqiang Zheng",
"Bo Zheng"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5116_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510188.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510188-supp.zip | 10.1007/978-3-030-58539-6_12 | null | null | Real-time video deblurring still remains a challenging task due to the complexity of spatially and temporally varying blur itself and the requirement of low computational cost. To improve the network efficiency, we adopt residual dense blocks into RNN cells, so as to efficiently extract the spatial features of the curr... |
5393_ECCV_2020_paper | Joint Semantic Instance Segmentation on Graphs with the Semantic Mutex Watershed | [
"Steffen Wolf",
"Yuyan Li",
"Constantin Pape",
"Alberto Bailoni",
"Anna Kreshuk",
"Fred A. Hamprecht"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5393_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510205.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510205-supp.pdf | 10.1007/978-3-030-58539-6_13 | 1912.12717 | title_judge | Semantic instance segmentation is the task of simultaneously partitioning an image into distinct segments while associating each pixel with a class label. In commonly used pipelines, segmentation and label assignment are solved separately since joint optimization is computationally expensive. We propose a greedy algori... |
5471_ECCV_2020_paper | Photon-Efficient 3D Imaging with A Non-Local Neural Network | [
"Jiayong Peng",
"Zhiwei Xiong",
"Xin Huang",
"Zheng-Ping Li",
"Dong Liu",
"Feihu Xu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5471_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510222.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510222-supp.pdf | 10.1007/978-3-030-58539-6_14 | null | null | Photon-efficient imaging has enabled a number of applications relying on single-photon sensors that can capture a 3D image with as few as one photon per pixel. In practice, however, measurements of low photon counts are often mixed with heavy background noise, which poses a great challenge for existing computational re... |
5554_ECCV_2020_paper | GeLaTO: Generative Latent Textured Objects | [
"Ricardo Martin-Brualla",
"Rohit Pandey",
"Sofien Bouaziz",
"Matthew Brown",
"Dan B Goldman"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5554_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510239.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510239-supp.zip | 10.1007/978-3-030-58539-6_15 | 2008.04852 | title_snapshot | Accurate modeling of 3D objects exhibiting transparency, reflections and thin structures is an extremely challenging problem. Inspired by billboards and geometric proxies used in computer graphics, this paper proposes Generative Latent Textured Objects (GeLaTO), a compact representation that combines a set of coarse sh... |
5672_ECCV_2020_paper | Improving Vision-and-Language Navigation with Image-Text Pairs from the Web | [
"Arjun Majumdar",
"Ayush Shrivastava",
"Stefan Lee",
"Peter Anderson",
"Devi Parikh",
"Dhruv Batra"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5672_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510256.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510256-supp.pdf | 10.1007/978-3-030-58539-6_16 | 2004.14973 | title_snapshot | Following a navigation instruction such as 'Walk down the stairs and stop at the brown sofa' requires embodied AI agents to ground referenced scene elements referenced (e.g. 'stairs') to visual content in the environment (pixels corresponding to 'stairs'). We ask the following question -- can we leverage abundant `dise... |
5685_ECCV_2020_paper | Directional Temporal Modeling for Action Recognition | [
"Xinyu Li",
"Bing Shuai",
"Joseph Tighe"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5685_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510273.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510273-supp.pdf | 10.1007/978-3-030-58539-6_17 | 2007.11040 | title_snapshot | Many current activity recognition models use 3D convolutional neural networks (e.g. I3D, I3D-NL) to generate local spatial-temporal features. However, such features do not encode clip-level ordered temporal information. In this paper, we introduce a channel independent directional convolution (CIDC) operation, which le... |
5714_ECCV_2020_paper | Shonan Rotation Averaging: Global Optimality by Surfing SO(p)(n) | [
"Frank Dellaert",
"David M. Rosen",
"Jing Wu",
"Robert Mahony",
"Luca Carlone"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5714_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510290.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510290-supp.pdf | 10.1007/978-3-030-58539-6_18 | 2008.02737 | title_snapshot | Shonan Rotation Averaging is a fast, simple, and elegant rotation averaging algorithm that is guaranteed to recover globally optimal solutions under mild assumptions on the measurement noise. Our method employs semidefinite relaxation in order to recover provably globally optimal solutions of the rotation averaging pro... |
5723_ECCV_2020_paper | Semantic Curiosity for Active Visual Learning | [
"Devendra Singh Chaplot",
"Helen Jiang",
"Saurabh Gupta",
"Abhinav Gupta"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5723_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510307.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510307-supp.zip | 10.1007/978-3-030-58539-6_19 | 2006.09367 | title_snapshot | In this paper, we study the task of embodied interactive learning for object detection. Given a set of environments (and some labeling budget), our goal is to learn an object detector by having an agent select what data to obtain labels for. How should an exploration policy decide which trajectory should be labeled? On... |
5821_ECCV_2020_paper | Multi-Temporal Recurrent Neural Networks For Progressive Non-Uniform Single Image Deblurring With Incremental Temporal Training | [
"Dongwon Park",
"Dong Un Kang",
"Jisoo Kim",
"Se Young Chun"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5821_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510324.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510324-supp.pdf | 10.1007/978-3-030-58539-6_20 | 1911.07410 | title_snapshot | Blind non-uniform image deblurring for severe blurs induced by large motions is still challenging. Multi-scale (MS) approach has been widely used for deblurring that sequentially recovers the downsampled original image in low spatial scale first and then further restores in high spatial scale using the result(s) from l... |
5975_ECCV_2020_paper | ProgressFace: Scale-Aware Progressive Learning for Face Detection | [
"Jiashu Zhu",
"Dong Li",
"Tiantian Han",
"Lu Tian",
"Yi Shan"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5975_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510341.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510341-supp.pdf | 10.1007/978-3-030-58539-6_21 | null | null | Scale variation stands out as one of key challenges in face detection. Recent attempts have been made to cope with this issue by incorporating image / feature pyramids or adjusting anchor sampling / matching strategies. In this work, we propose a novel scale-aware progressive training mechanism to address large scale v... |
6025_ECCV_2020_paper | Learning Multi-layer Latent Variable Model via Variational Optimization of Short Run MCMC for Approximate Inference | [
"Erik Nijkamp",
"Bo Pang",
"Tian Han",
"Linqi Zhou",
"Song-Chun Zhu",
"Ying Nian Wu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6025_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510358.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510358-supp.pdf | 10.1007/978-3-030-58539-6_22 | 1912.01909 | title_snapshot | This paper studies the fundamental problem of learning deep generative models that consist of multiple layers of latent variables organized in top-down architectures. Such models have high expressivity and allow for learning hierarchical representations. Learning such a generative model requires inferring the latent va... |
6053_ECCV_2020_paper | CoTeRe-Net: Discovering Collaborative Ternary Relations in Videos | [
"Zhensheng Shi",
"Cheng Guan",
"Liangjie Cao",
"Qianqian Li",
"Ju Liang",
"Zhaorui Gu",
"Haiyong Zheng",
"Bing Zheng"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6053_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510375.pdf | null | 10.1007/978-3-030-58539-6_23 | null | null | Modeling relations is crucial to understand videos for action and behavior recognition. Current relation models mainly reason about relations of invisibly implicit cues, while important relations of visually explicit cues are rarely considered, and the collaboration between them is usually ignored. In this paper, we pr... |
6100_ECCV_2020_paper | Modeling the Effects of Windshield Refraction for Camera Calibration | [
"Frank Verbiest",
"Marc Proesmans",
"Luc Van Gool"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6100_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510392.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510392-supp.zip | 10.1007/978-3-030-58539-6_24 | null | null | In this paper, we study the effects of windshield refraction for autonomous driving applications. These distortion effects are surprisingly large and can not be explained by traditional camera models. Instead of using a generalized camera approach, we propose a novel approach to jointly optimize a traditional camera mo... |
6124_ECCV_2020_paper | Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search | [
"Prashant Pandey",
"Aayush Kumar Tyagi",
"Sameer Ambekar",
"Prathosh AP"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6124_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510409.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510409-supp.pdf | 10.1007/978-3-030-58539-6_25 | 2006.08696 | title_snapshot | Segmentation of the pixels corresponding to human skin is an essential first step in multiple applications ranging from surveillance to heart-rate estimation from remote-photoplethysmography. However, the existing literature considers the problem only in the visible-range of the EM-spectrum which limits their utility i... |
6254_ECCV_2020_paper | PROFIT: A Novel Training Method for sub-4-bit MobileNet Models | [
"Eunhyeok Park",
"Sungjoo Yoo"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6254_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510426.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510426-supp.pdf | 10.1007/978-3-030-58539-6_26 | 2008.04693 | title_snapshot | 4-bit and lower precision mobile models are required due to the ever-increasing demand for better energy efficiency in mobile devices. In this work, we report that the activation instability induced by weight quantization (AIWQ) is the key obstacle to sub-4-bit quantization of mobile networks. To alleviate the AIWQ pro... |
6277_ECCV_2020_paper | Visual Relation Grounding in Videos | [
"Junbin Xiao",
"Xindi Shang",
"Xun Yang",
"Sheng Tang",
"Tat-Seng Chua"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6277_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510443.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510443-supp.pdf | 10.1007/978-3-030-58539-6_27 | 2007.08814 | title_snapshot | In this paper, we explore a novel task named visual Relation Grounding in Videos (vRGV). The task aims at spatio-temporally localizing the given relations in the form of subject-predicate-object in the videos, so as to provide supportive visual facts for other high-level video-language tasks (e.g., video-language groun... |
6296_ECCV_2020_paper | Weakly Supervised 3D Human Pose and Shape Reconstruction with Normalizing Flows | [
"Andrei Zanfir",
"Eduard Gabriel Bazavan",
"Hongyi Xu",
"William T. Freeman",
"Rahul Sukthankar",
"Cristian Sminchisescu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6296_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510460.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510460-supp.pdf | 10.1007/978-3-030-58539-6_28 | 2003.10350 | title_snapshot | Monocular 3D human pose and shape estimation is challenging due to the many degrees of freedom of the human body and the difficulty to acquire training data for large-scale supervised learning in complex visual scenes where humans with diverse shape and appearance, appear against complex backgrounds,in a variety of pos... |
6314_ECCV_2020_paper | Controlling Style and Semantics in Weakly-Supervised Image Generation | [
"Dario Pavllo",
"Aurelien Lucchi",
"Thomas Hofmann"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6314_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510477.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510477-supp.zip | 10.1007/978-3-030-58539-6_29 | 1912.03161 | title_snapshot | We propose a weakly-supervised approach for conditional image generation of complex scenes where a user has fine control over objects appearing in the scene. We exploit sparse semantic maps to control object shapes and classes, as well as textual descriptions or attributes to control both local and global style. In ord... |
6360_ECCV_2020_paper | Jointly learning visual motion and confidence from local patches in event cameras | [
"Daniel R. Kepple",
"Daewon Lee",
"Colin Prepsius",
"Volkan Isler",
"Il Memming Park",
"Daniel D. Lee"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6360_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510494.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510494-supp.pdf | 10.1007/978-3-030-58539-6_30 | null | null | We propose the first network to jointly learn visual motion and confidence from events in spatially local patches. Event-based sensors deliver high temporal resolution motion information in a sparse, non-redundant format. This creates the potential for low computation, low latency motion recognition. Neural networks wh... |
6406_ECCV_2020_paper | SODA: Story Oriented Dense Video Captioning Evaluation Framework | [
"Soichiro Fujita",
"Tsutomu Hirao",
"Hidetaka Kamigaito",
"Manabu Okumura",
"Masaaki Nagata"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6406_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510511.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510511-supp.pdf | 10.1007/978-3-030-58539-6_31 | null | null | Dense Video Captioning (DVC) is a challenging task that localizes all events in a short video and describes them with natural language sentences. The main goal of DVC is video story description, that is, to generate a concise video story that supports human video comprehension without watching it. In recent years, DVC ... |
6490_ECCV_2020_paper | Sketch-Guided Object Localization in Natural Images | [
"Aditay Tripathi",
"Rajath R. Dani",
"Anand Mishra and Anirban Chakraborty"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6490_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510528.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510528-supp.pdf | 10.1007/978-3-030-58539-6_32 | 2008.06551 | title_snapshot | We introduce a novel problem of localizing all the instances of an object (seen or unseen during training) in a natural image via sketch query. We refer to this problem as sketch-guided object localization. This problem is distinctively different from the traditional sketch-based image retrieval task where the gallery ... |
6496_ECCV_2020_paper | A unifying mutual information view of metric learning: cross-entropy vs. pairwise losses | [
"Malik Boudiaf",
"Jérôme Rony",
"Imtiaz Masud Ziko",
"Eric Granger",
"Marco Pedersoli",
"Pablo Piantanida",
"Ismail Ben Ayed"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6496_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510545.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510545-supp.pdf | 10.1007/978-3-030-58539-6_33 | 2003.08983 | title_snapshot | Recently, substantial research efforts in Deep Metric Learning (DML) focused on designing complex pairwise-distance losses, which require convoluted schemes to ease optimization, such as sample mining or pair weighting. The standard cross-entropy loss for classification has been largely overlooked in DML. On the surfac... |
6959_ECCV_2020_paper | Behind the Scene: Revealing the Secrets of Pre-trained Vision-and-Language Models | [
"Jize Cao",
"Zhe Gan",
"Yu Cheng",
"Licheng Yu",
"Yen-Chun Chen",
"Jingjing Liu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6959_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510562.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510562-supp.pdf | 10.1007/978-3-030-58539-6_34 | 2005.07310 | title_snapshot | Recent Transformer-based large-scale pre-trained models have revolutionized vision-and-language (V+L) research. Models such as ViLBERT, LXMERT and UNITER have significantly lifted state of the art across a wide range of V+L benchmarks. However, little is known about the inner mechanisms that destine their impressive su... |
7231_ECCV_2020_paper | The Hessian Penalty: A Weak Prior for Unsupervised Disentanglement | [
"William Peebles",
"John Peebles",
"Jun-Yan Zhu",
"Alexei Efros",
"Antonio Torralba"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/7231_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510579.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510579-supp.zip | 10.1007/978-3-030-58539-6_35 | 2008.10599 | title_snapshot | Existing popular methods for disentanglement rely on hand-picked priors and complex encoder-based architectures. In this paper, we propose the Hessian Penalty, a simple regularization function that encourages the input Hessian of a function to be diagonal. Our method is completely model-agnostic and can be applied to a... |
5_ECCV_2020_paper | STAR: Sparse Trained Articulated Human Body Regressor | [
"Ahmed A. A. Osman",
"Timo Bolkart",
"Michael J. Black"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/5_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510596.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510596-supp.pdf | 10.1007/978-3-030-58539-6_36 | 2008.08535 | title_snapshot | The SMPL body model is widely used for the estimation, synthesis, and analysis of 3D human pose and shape. While popular, we show that SMPL has several limitations and introduce STAR, which is quantitatively and qualitatively superior to SMPL. First, SMPL has a huge number of parameters resulting from its use of global... |
13_ECCV_2020_paper | Optical Flow Distillation: Towards Efficient and Stable Video Style Transfer | [
"Xinghao Chen",
"Yiman Zhang",
"Yunhe Wang",
"Han Shu",
"Chunjing Xu",
"Chang Xu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/13_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510613.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510613-supp.zip | 10.1007/978-3-030-58539-6_37 | 2007.05146 | title_snapshot | Video style transfer techniques inspire many exciting applications on mobile devices. However, their efficiency and stability are still far from satisfactory. To boost the transfer stability across frames, optical flow is widely adopted, despite its high computational complexity, e.g., occupying over 97% inference time... |
15_ECCV_2020_paper | Collaboration by Competition: Self-coordinated Knowledge Amalgamation for Multi-talent Student Learning | [
"Sihui Luo",
"Wenwen Pan",
"Xinchao Wang",
"Dazhou Wang",
"Haihong Tang",
"Mingli Song"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/15_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510630.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510630-supp.pdf | 10.1007/978-3-030-58539-6_38 | null | null | A vast number of well-trained deep networks have been released by developers online for plug-and-play use. These networks specialize in different tasks and in many cases, the data and annotations used to train them are not publicly available. In this paper, we study how to reuse such heterogeneous pre-trained models as... |
25_ECCV_2020_paper | Do Not Disturb Me: Person Re-identification Under the Interference of Other Pedestrians | [
"Shizhen Zhao",
"Changxin Gao",
"Jun Zhang",
"Hao Cheng",
"Chuchu Han",
"Xinyang Jiang",
"Xiaowei Guo",
"Wei-Shi Zheng",
"Nong Sang",
"Xing Sun"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/25_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510647.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510647-supp.pdf | 10.1007/978-3-030-58539-6_39 | 2008.06963 | title_snapshot | In the conventional person Re-ID setting, it is assumed that cropped images are the person images within the bounding box for each individual. However, in a crowded scene, off-shelf-detectors may generate bounding boxes involving multiple people, where the large proportion of background pedestrians or human occlusion e... |
31_ECCV_2020_paper | Learning 3D Part Assembly from a Single Image | [
"Yichen Li",
"Kaichun Mo",
"Lin Shao",
"Minhyuk Sung",
"Leonidas Guibas"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/31_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510664.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510664-supp.pdf | 10.1007/978-3-030-58539-6_40 | 2003.09754 | title_snapshot | Autonomous assembly is a crucial capability for robots in many applications. For this task, several problems such as obstacle avoidance, motion planning, and actuator control have been extensively studied in robotics. However, when it comes to task specification, the space of possibilities remains under-explored. Towar... |
32_ECCV_2020_paper | PT2PC: Learning to Generate 3D Point Cloud Shapes from Part Tree Conditions | [
"Kaichun Mo",
"He Wang",
"Xinchen Yan",
"Leonidas Guibas"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/32_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510681.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510681-supp.pdf | 10.1007/978-3-030-58539-6_41 | 2003.08624 | title_snapshot | Generative 3D shape modeling is a fundamental research area in computer vision and interactive computer graphics, with many real-world applications. This paper investigates the novel problem of generating a 3D point cloud geometry for a shape from a symbolic part tree representation. In order to learn such a conditiona... |
50_ECCV_2020_paper | Highly Efficient Salient Object Detection with 100K Parameters | [
"Shang-Hua Gao",
"Yong-Qiang Tan",
"Ming-Ming Cheng",
"Chengze Lu",
"Yunpeng Chen",
"Shuicheng Yan"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/50_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510698.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510698-supp.pdf | 10.1007/978-3-030-58539-6_42 | 2003.05643 | title_snapshot | Salient object detection models often demand a considerable amount of computation cost to make precise prediction for each pixel, making them hardly applicable on low-power devices. In this paper, we aim to relieve the contradiction between computation cost and model performance by improving the network efficiency to a... |
69_ECCV_2020_paper | HardGAN: A Haze-Aware Representation Distillation GAN for Single Image Dehazing | [
"Qili Deng",
"Ziling Huang",
"Chung-Chi Tsai",
"Chia-Wen Lin"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/69_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510715.pdf | null | 10.1007/978-3-030-58539-6_43 | null | null | In this paper, we present a Haze-Aware Representation Distillation Generative Adversarial Network named HardGAN for single-image dehazing. Unlike previous studies that intend to model the transmission map and global atmospheric light jointly to restore a clear image, we solve this regression problem by a multi-scale st... |
88_ECCV_2020_paper | Lifespan Age Transformation Synthesis | [
"Roy Or-El",
"Soumyadip Sengupta",
"Ohad Fried",
"Eli Shechtman",
"Ira Kemelmacher-Shlizerman"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/88_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510732.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510732-supp.zip | 10.1007/978-3-030-58539-6_44 | 2003.09764 | title_snapshot | We address the problem of single photo age progression and regression---the prediction of how a person might look in the future, or how they looked in the past. Most existing aging methods are limited to changing the texture, overlooking transformations in head shape that occur during the human aging and growth process... |
90_ECCV_2020_paper | Domain2Vec: Domain Embedding for Unsupervised Domain Adaptation | [
"Xingchao Peng",
"Yichen Li",
"Kate Saenko"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/90_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510749.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510749-supp.pdf | 10.1007/978-3-030-58539-6_45 | 2007.09257 | title_snapshot | Conventional unsupervised domain adaptation (UDA) studies the knowledge transfer between a limited number of domains. This neglects the more practical scenario where data are distributed in numerous different domains in the real world. The domain similarity between those domains is critical for domain adaptation perfor... |
106_ECCV_2020_paper | Simulating Content Consistent Vehicle Datasets with Attribute Descent | [
"Yue Yao",
"Liang Zheng",
"Xiaodong Yang",
"Milind Naphade",
"Tom Gedeon"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/106_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510766.pdf | null | 10.1007/978-3-030-58539-6_46 | 1912.08855 | title_snapshot | This paper uses a graphic engine to simulate a large amount of training data with free annotations. Between synthetic and real data, there is a two-level domain gap, i.e., content level and appearance level. While the latter has been widely studied, we focus on reducing the content gap in attributes like illumination a... |
116_ECCV_2020_paper | Multiview Detection with Feature Perspective Transformation | [
"Yunzhong Hou",
"Liang Zheng",
"Stephen Gould"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/116_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520001.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520001-supp.zip | 10.1007/978-3-030-58571-6_1 | 2007.07247 | title_snapshot | Incorporating multiple camera views for detection alleviates the impact of occlusions in crowded scenes. In a multiview detection system, we need to answer two important questions. First, how should we aggregate cues from multiple views? Second, how should we aggregate information from spatially neighboring locations? ... |
121_ECCV_2020_paper | Learning Object Relation Graph and Tentative Policy for Visual Navigation | [
"Heming Du",
"Xin Yu",
"Liang Zheng"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/121_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520018.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520018-supp.zip | 10.1007/978-3-030-58571-6_2 | 2007.11018 | title_snapshot | Target-driven visual navigation aims at navigating an agent towards a given target based on the observation of the agent. In this task, it is critical to learn informative visual representation and robust navigation policy. Aiming to improve these two components, this paper proposes three complementary techniques, obje... |
123_ECCV_2020_paper | Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition | [
"Chenyang Si",
"Xuecheng Nie",
"Wei Wang",
"Liang Wang",
"Tieniu Tan",
"Jiashi Feng"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/123_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520035.pdf | null | 10.1007/978-3-030-58571-6_3 | 2007.05934 | title_snapshot | We consider the problem of semi-supervised 3D action recognition which has been rarely explored before. Its major challenge lies in how to effectively learn motion representations from unlabeled data. Self-supervised learning (SSL) has been proved very effective at learning representations from unlabeled data in the im... |
132_ECCV_2020_paper | Across Scales & Across Dimensions: Temporal Super-Resolution using Deep Internal Learning | [
"Liad Pollak Zuckerman",
"Eyal Naor",
"George Pisha",
"Shai Bagon",
"Michal Irani"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/132_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520052.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520052-supp.zip | 10.1007/978-3-030-58571-6_4 | 2003.08872 | title_snapshot | When a very fast dynamic event is recorded with a low-framerate camera, the resulting video suffers from severe motion blur (due to exposure time) and motion aliasing (due to low sampling rate in time). True Temporal Super-Resolution (TSR) is more than just Temporal-Interpolation (increasing framerate). It can also rec... |
138_ECCV_2020_paper | Inducing Optimal Attribute Representations for Conditional GANs | [
"Binod Bhattarai",
"Tae-Kyun Kim"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/138_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520069.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520069-supp.pdf | 10.1007/978-3-030-58571-6_5 | 2003.06472 | title_snapshot | Conditional GANs (cGANs) are widely used in translating an image from one category to another. Meaningful conditions on GANsprovide greater flexibility and control over the nature of the target domain synthetic data. Existing conditional GANs commonly encode target domain label information as hard-coded categorical vec... |
152_ECCV_2020_paper | AR-Net: Adaptive Frame Resolution for Efficient Action Recognition | [
"Yue Meng",
"Chung-Ching Lin",
"Rameswar Panda",
"Prasanna Sattigeri",
"Leonid Karlinsky",
"Aude Oliva",
"Kate Saenko",
"Rogerio Feris"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/152_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520086.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520086-supp.pdf | 10.1007/978-3-030-58571-6_6 | 2007.15796 | title_snapshot | Action recognition is an open and challenging problem in computer vision. While current state-of-the-art models offer excellent recognition results, their computational expense limits their impact for many real-world applications. In this paper, we propose a novel approach, called AR-Net (Adaptive Resolution Network), ... |
156_ECCV_2020_paper | Image-to-Voxel Model Translation for 3D Scene Reconstruction and Segmentation | [
"Vladimir V. Kniaz",
"Vladimir A. Knyaz",
"Fabio Remondino",
"Artem Bordodymov",
"Petr Moshkantsev"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/156_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520103.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520103-supp.zip | 10.1007/978-3-030-58571-6_7 | null | null | Objects class, depth, and shape are instantly reconstructed by a human looking at a 2D image. While modern deep models solve each of these challenging tasks separately, they struggle to perform simultaneous scene 3D reconstruction and segmentation. We propose a single shot image-to-semantic voxel model translation fram... |
157_ECCV_2020_paper | Consistency Guided Scene Flow Estimation | [
"Yuhua Chen",
"Luc Van Gool",
"Cordelia Schmid",
"Cristian Sminchisescu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/157_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520120.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520120-supp.pdf | 10.1007/978-3-030-58571-6_8 | 2006.11242 | title_snapshot | Consistency Guided Scene Flow Estimation (CGSF) is a self-supervised framework for the joint reconstruction of 3D scene structure and motion from stereo video. The model takes two temporal stereo pairs as input, and predicts disparity and scene flow. The model self-adapts at test time by iteratively refining its predic... |
160_ECCV_2020_paper | Autoregressive Unsupervised Image Segmentation | [
"Yassine Ouali",
"Céline Hudelot",
"Myriam Tami"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/160_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520137.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520137-supp.pdf | 10.1007/978-3-030-58571-6_9 | 2007.08247 | title_snapshot | In this work, we propose a new unsupervised image segmentation approach based on mutual information maximization between different constructed views of the inputs. Taking inspiration from autoregressive generative models, that predict the current pixel from past pixels in a raster-scan ordering created with masked conv... |
169_ECCV_2020_paper | Controllable Image Synthesis via SegVAE | [
"Yen-Chi Cheng",
"Hsin-Ying Lee",
"Min Sun",
"Ming-Hsuan Yang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/169_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520154.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520154-supp.pdf | 10.1007/978-3-030-58571-6_10 | 2007.08397 | title_snapshot | Flexible user controls are desirable for content creation and image editing. A semantic map is commonly used intermediate representation for conditional image generation. Compared to the operation on raw RGB pixels, the semantic map enables simpler user modification. In this work, we specifically target at generating s... |
173_ECCV_2020_paper | Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search | [
"Yuan Tian",
"Qin Wang",
"Zhiwu Huang",
"Wen Li",
"Dengxin Dai",
"Minghao Yang",
"Jun Wang",
"Olga Fink"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/173_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520171.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520171-supp.pdf | 10.1007/978-3-030-58571-6_11 | 2007.09180 | title_snapshot | In this paper, we introduce a new reinforcement learning (RL) based neural architecture search (NAS) methodology for effective and efficient generative adversarial network (GAN) architecture search. The key idea is to formulate the GAN architecture search problem as a Markov decision process (MDP) for smoother architec... |
177_ECCV_2020_paper | Efficient Non-Line-of-Sight Imaging from Transient Sinograms | [
"Mariko Isogawa",
"Dorian Chan",
"Ye Yuan",
"Kris Kitani",
"Matthew O’Toole"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/177_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520188.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520188-supp.zip | 10.1007/978-3-030-58571-6_12 | 2008.02787 | title_snapshot | Non-line-of-sight (NLOS) imaging techniques use light that diffusely reflects off of visible surfaces (e.g., walls) to see around corners. One approach involves using pulsed lasers and ultrafast sensors to measure the travel time of multiply scattered light. Unlike existing NLOS techniques that generally require densel... |
181_ECCV_2020_paper | Texture Hallucination for Large-Factor Painting Super-Resolution | [
"Yulun Zhang",
"Zhifei Zhang",
"Stephen DiVerdi",
"Zhaowen Wang",
"Jose Echevarria",
"Yun Fu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/181_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520205.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520205-supp.pdf | 10.1007/978-3-030-58571-6_13 | 1912.00515 | title_snapshot | We aim to super-resolve digital paintings, synthesizing realistic details from high-resolution reference painting materials for very large scaling factors (g 8$ imes$, 16$ imes$). However, previous single image super-resolution (SISR) methods would either lose textural details or introduce unpleasing artifacts. On the... |
183_ECCV_2020_paper | Learning Progressive Joint Propagation for Human Motion Prediction | [
"Yujun Cai",
"Lin Huang",
"Yiwei Wang",
"Tat-Jen Cham",
"Jianfei Cai",
"Junsong Yuan",
"Jun Liu",
"Xu Yang",
"Yiheng Zhu",
"Xiaohui Shen",
"Ding Liu",
"Jing Liu",
"Nadia Magnenat Thalmann"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/183_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520222.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520222-supp.pdf | 10.1007/978-3-030-58571-6_14 | null | null | Despite the great progress in human motion prediction, it remains a challenging task due to the complicated structural dynamics of human behaviors. In this paper, we address this problem in three aspects. First, to capture the long-range spatial correlations and temporal dependencies, we apply a transformer-based archi... |
184_ECCV_2020_paper | Image Stitching and Rectification for Hand-Held Cameras | [
"Bingbing Zhuang",
"Quoc-Huy Tran"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/184_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520239.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520239-supp.zip | 10.1007/978-3-030-58571-6_15 | 2008.09229 | title_snapshot | In this paper, we derive a new differential homography that can account for the scanline-varying camera poses in Rolling Shutter (RS) cameras, and demonstrate its application to carry out RS-aware image stitching and rectification at one stroke. Despite the high complexity of RS geometry, we focus in this paper on a sp... |
186_ECCV_2020_paper | ParSeNet: A Parametric Surface Fitting Network for 3D Point Clouds | [
"Gopal Sharma",
"Difan Liu",
"Subhransu Maji",
"Evangelos Kalogerakis",
"Siddhartha Chaudhuri",
"Radomír Měch"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/186_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520256.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520256-supp.pdf | 10.1007/978-3-030-58571-6_16 | 2003.12181 | title_snapshot | We propose a novel, end-to-end trainable, deep network called ParSeNet that decomposes a 3D point cloud into parametric surface patches, including B-spline patches as well as basic geometric primitives. ParSeNet is trained on a large-scale dataset of man-made 3D shapes and captures high-level semantic priors for shape ... |
188_ECCV_2020_paper | The Group Loss for Deep Metric Learning | [
"Ismail Elezi",
"Sebastiano Vascon",
"Alessandro Torcinovich",
"Marcello Pelillo",
"Laura Leal-Taixé"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/188_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520273.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520273-supp.pdf | 10.1007/978-3-030-58571-6_17 | 1912.00385 | title_snapshot | Deep metric learning has yielded impressive results in tasks such as clustering and image retrieval by leveraging neural networks to obtain highly discriminative feature embeddings, which can be used to group samples into different classes. Much research has been devoted to the design of smart loss functions or data mi... |
203_ECCV_2020_paper | Learning Object Depth from Camera Motion and Video Object Segmentation | [
"Brent A. Griffin",
"Jason J. Corso"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/203_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520290.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520290-supp.pdf | 10.1007/978-3-030-58571-6_18 | 2007.05676 | title_snapshot | Video object segmentation, i.e., the separation of a target object from background in video, has made significant progress on real and challenging videos in recent years. To leverage this progress in 3D applications, this paper addresses the problem of learning to estimate the depth of segmented objects given some meas... |
206_ECCV_2020_paper | OnlineAugment: Online Data Augmentation with Less Domain Knowledge | [
"Zhiqiang Tang",
"Yunhe Gao",
"Leonid Karlinsky",
"Prasanna Sattigeri",
"Rogerio Feris",
"Dimitris Metaxas"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/206_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520307.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520307-supp.zip | 10.1007/978-3-030-58571-6_19 | 2007.09271 | title_snapshot | Data augmentation is one of the most important tools in training modern deep neural networks. Recently, great advances have been made in searching for optimal augmentation policies in the image classification domain. However, two key points related to data augmentation remain uncovered by the current methods. First is ... |
209_ECCV_2020_paper | Learning Pairwise Inter-Plane Relations for Piecewise Planar Reconstruction | [
"Yiming Qian",
"Yasutaka Furukawa"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/209_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520324.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520324-supp.zip | 10.1007/978-3-030-58571-6_20 | null | null | This paper proposes a novel single-image piecewise planar reconstruction technique that infers and enforces inter-plane relationships. Our approach takes a planar reconstruction result from an existing system, then utilizes convolutional neural network (CNN) to (1) classify if two planes are orthogonal or parallel; and... |
230_ECCV_2020_paper | Intra-class Feature Variation Distillation for Semantic Segmentation | [
"Yukang Wang",
"Wei Zhou",
"Tao Jiang",
"Xiang Bai",
"Yongchao Xu"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/230_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520341.pdf | null | 10.1007/978-3-030-58571-6_21 | null | null | Current state-of-the-art semantic segmentation methods usually require high computational resources for accurate segmentation. One promising way to achieve a good trade-off between segmentation accuracy and efficiency is knowledge distillation. In this paper, different from previous methods performing knowledge distill... |
233_ECCV_2020_paper | Temporal Distinct Representation Learning for Action Recognition | [
"Junwu Weng",
"Donghao Luo",
"Yabiao Wang",
"Ying Tai",
"Chengjie Wang",
"Jilin Li",
"Feiyue Huang",
"Xudong Jiang",
"Junsong Yuan"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/233_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520358.pdf | null | 10.1007/978-3-030-58571-6_22 | 2007.07626 | title_snapshot | Motivated by the previous success of Two-Dimensional Convolutional Neural Network (2D CNN) on image recognition, researchers endeavor to leverage it to characterize videos. However, one limitation of applying 2D CNN to analyze videos is that different frames of a video share the same 2D CNN kernels, which may result in... |
241_ECCV_2020_paper | Representative Graph Neural Network | [
"Changqian Yu",
"Yifan Liu",
"Changxin Gao",
"Chunhua Shen",
"Nong Sang"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/241_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520375.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520375-supp.zip | 10.1007/978-3-030-58571-6_23 | 2008.05202 | title_snapshot | Non-local operation is widely explored to model the long-range dependencies. However, the redundant computation in this operation leads to a prohibitive complexity. In this paper, we present a Representative Graph (RepGraph) layer to dynamically sample a few representative features, which dramatically reduces redundanc... |
264_ECCV_2020_paper | Deformation-Aware 3D Model Embedding and Retrieval | [
"Mikaela Angelina Uy",
"Jingwei Huang",
"Minhyuk Sung",
"Tolga Birdal",
"Leonidas Guibas"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/264_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520392.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520392-supp.zip | 10.1007/978-3-030-58571-6_24 | 2004.01228 | title_snapshot | We introduce a new problem of mph{retrieving} 3D models that are mph{deformable} to a given query shape and present a novel deep mph{deformation-aware} embedding to solve this retrieval task. 3D model retrieval is a fundamental operation for recovering a clean and complete 3D model from a noisy and partial 3D scan. ... |
277_ECCV_2020_paper | Atlas: End-to-End 3D Scene Reconstruction from Posed Images | [
"Zak Murez",
"Tarrence van As",
"James Bartolozzi",
"Ayan Sinha",
"Vijay Badrinarayanan",
"Andrew Rabinovich"
] | https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/277_ECCV_2020_paper.php | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520409.pdf | https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123520409-supp.zip | 10.1007/978-3-030-58571-6_25 | 2003.10432 | title_snapshot | We present an end-to-end 3D reconstruction of a scene by directly regressing a truncated signed distance function (TSDF) from a set of posed RGB images. Traditional approaches to 3D reconstruction rely on an intermediate representation of depth maps prior to estimating a full 3D model of a scene. We hypothesize that a ... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.