paper_id stringlengths 47 136 | title stringlengths 25 151 | authors listlengths 1 13 | cvf_url stringlengths 104 193 | pdf_url stringlengths 105 194 | supp_url stringlengths 101 148 ⌀ | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 3
values | bibtex large_stringlengths 309 566 | abstract large_stringlengths 683 2.58k |
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Wang_VM-Gait_Multi-Modal_3D_Representation_Based_on_Virtual_Marker_for_Gait_WACV_2025_paper | VM-Gait: Multi-Modal 3D Representation Based on Virtual Marker for Gait Recognition | [
"Zhao-Yang Wang",
"Jiang Liu",
"Jieneng Chen",
"Rama Chellappa"
] | https://openaccess.thecvf.com/content/WACV2025/html/Wang_VM-Gait_Multi-Modal_3D_Representation_Based_on_Virtual_Marker_for_Gait_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Wang_VM-Gait_Multi-Modal_3D_Representation_Based_on_Virtual_Marker_for_Gait_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Wang_VM-Gait_Multi-Modal_3D_WACV_2025_supplemental.pdf | null | null | @InProceedings{Wang_2025_WACV,
author = {Wang, Zhao-Yang and Liu, Jiang and Chen, Jieneng and Chellappa, Rama},
title = {VM-Gait: Multi-Modal 3D Representation Based on Virtual Marker for Gait Recognition},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
... | Gait recognition plays a vital role in biometric applications by analyzing the unique characteristics of an individual's walking pattern. Methods based on 2D representations such as silhouettes and skeletons are increasingly being developed to learn the shape features and joint dynamic movements. Nevertheless the effec... |
Saito_Point-JEPA_A_Joint_Embedding_Predictive_Architecture_for_Self-Supervised_Learning_on_WACV_2025_paper | Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud | [
"Ayumu Saito",
"Prachi Kudeshia",
"Jiju Poovvancheri"
] | https://openaccess.thecvf.com/content/WACV2025/html/Saito_Point-JEPA_A_Joint_Embedding_Predictive_Architecture_for_Self-Supervised_Learning_on_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Saito_Point-JEPA_A_Joint_Embedding_Predictive_Architecture_for_Self-Supervised_Learning_on_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Saito_Point-JEPA_A_Joint_WACV_2025_supplemental.pdf | 2404.16432 | title_snapshot | @InProceedings{Saito_2025_WACV,
author = {Saito, Ayumu and Kudeshia, Prachi and Poovvancheri, Jiju},
title = {Point-JEPA: A Joint Embedding Predictive Architecture for Self-Supervised Learning on Point Cloud},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)... | Recent advancements in self-supervised learning in the point cloud domain have demonstrated significant potential. However these methods often suffer from drawbacks such as lengthy pre-training time the necessity of reconstruction in the input space and the necessity of additional modalities. In order to address these ... |
Agrawal_CM3T_Framework_for_Efficient_Multimodal_Learning_for_Inhomogeneous_Interaction_Datasets_WACV_2025_paper | CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets | [
"Tanay Agrawal",
"Mohammed Guermal",
"Michal Balazia",
"Francois Bremond"
] | https://openaccess.thecvf.com/content/WACV2025/html/Agrawal_CM3T_Framework_for_Efficient_Multimodal_Learning_for_Inhomogeneous_Interaction_Datasets_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Agrawal_CM3T_Framework_for_Efficient_Multimodal_Learning_for_Inhomogeneous_Interaction_Datasets_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Agrawal_CM3T_Framework_for_WACV_2025_supplemental.pdf | 2501.03332 | cvf | @InProceedings{Agrawal_2025_WACV,
author = {Agrawal, Tanay and Guermal, Mohammed and Balazia, Michal and Bremond, Francois},
title = {CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets},
booktitle = {Proceedings of the Winter Conference on Applications of Compute... | Challenges in cross-learning involve inhomogeneous or even inadequate amount of training data and lack of resources for retraining large pretrained models. Inspired by transfer learning techniques in NLP adapters and prefix tuning this paper presents a new model-agnostic plugin architecture for cross-learning called CM... |
Roh_CTIP_Towards_Accurate_Tabular-to-Image_Generation_for_Tire_Footprint_Generation_WACV_2025_paper | CTIP: Towards Accurate Tabular-to-Image Generation for Tire Footprint Generation | [
"Daeyoung Roh",
"Donghee Han",
"Jihyun Nam",
"Jungsoo Oh",
"Youngbin You",
"Jeongheon Park",
"Mun Yi"
] | https://openaccess.thecvf.com/content/WACV2025/html/Roh_CTIP_Towards_Accurate_Tabular-to-Image_Generation_for_Tire_Footprint_Generation_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Roh_CTIP_Towards_Accurate_Tabular-to-Image_Generation_for_Tire_Footprint_Generation_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Roh_CTIP_Towards_Accurate_WACV_2025_supplemental.pdf | null | null | @InProceedings{Roh_2025_WACV,
author = {Roh, Daeyoung and Han, Donghee and Nam, Jihyun and Oh, Jungsoo and You, Youngbin and Park, Jeongheon and Yi, Mun},
title = {CTIP: Towards Accurate Tabular-to-Image Generation for Tire Footprint Generation},
booktitle = {Proceedings of the Winter Conference on A... | Generating images directly from tabular data while ensuring an accurate representation of ground truth is a useful application in manufacturing. Simply embedding tabular data to use it as a condition in image generation models often fails to learn the correspondence between tabular features and their impact on the gene... |
Gupta_CIRCOD_Co-Saliency_Inspired_Referring_Camouflaged_Object_Discovery_WACV_2025_paper | CIRCOD: Co-Saliency Inspired Referring Camouflaged Object Discovery | [
"Avi Gupta",
"Koteswar Rao Jerripothula",
"Tammam Tillo"
] | https://openaccess.thecvf.com/content/WACV2025/html/Gupta_CIRCOD_Co-Saliency_Inspired_Referring_Camouflaged_Object_Discovery_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Gupta_CIRCOD_Co-Saliency_Inspired_Referring_Camouflaged_Object_Discovery_WACV_2025_paper.pdf | null | null | null | @InProceedings{Gupta_2025_WACV,
author = {Gupta, Avi and Jerripothula, Koteswar Rao and Tillo, Tammam},
title = {CIRCOD: Co-Saliency Inspired Referring Camouflaged Object Discovery},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {Februar... | Camouflaged object detection (COD) the task of identifying objects concealed within their surroundings is often quite challenging due to the similarity that exists between the foreground and background. By incorporating an additional referring image where the target object is clearly visible we can leverage the similar... |
McGriff_Dense_Scene_Reconstruction_from_Light-Field_Images_Affected_by_Rolling_Shutter_WACV_2025_paper | Dense Scene Reconstruction from Light-Field Images Affected by Rolling Shutter | [
"Hermes McGriff",
"Renato Martins",
"Nicolas Andreff",
"Cedric Demonceaux"
] | https://openaccess.thecvf.com/content/WACV2025/html/McGriff_Dense_Scene_Reconstruction_from_Light-Field_Images_Affected_by_Rolling_Shutter_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/McGriff_Dense_Scene_Reconstruction_from_Light-Field_Images_Affected_by_Rolling_Shutter_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/McGriff_Dense_Scene_Reconstruction_WACV_2025_supplemental.pdf | 2412.03518 | cvf | @InProceedings{McGriff_2025_WACV,
author = {McGriff, Hermes and Martins, Renato and Andreff, Nicolas and Demonceaux, Cedric},
title = {Dense Scene Reconstruction from Light-Field Images Affected by Rolling Shutter},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision ... | This paper presents a dense depth estimation approach from light-field (LF) images that is able to compensate for strong rolling shutter (RS) effects. Our method estimates RS compensated views and dense RS compensated disparity maps. We present a two-stage method based on a 2D Gaussians Splatting that allows for a "ren... |
Liang_GauFRe_Gaussian_Deformation_Fields_for_Real-Time_Dynamic_Novel_View_Synthesis_WACV_2025_paper | GauFRe: Gaussian Deformation Fields for Real-Time Dynamic Novel View Synthesis | [
"Yiqing Liang",
"Numair Khan",
"Zhengqin Li",
"Thu H Nguyen-Phuoc",
"Douglas Lanman",
"James Tompkin",
"Lei Xiao"
] | https://openaccess.thecvf.com/content/WACV2025/html/Liang_GauFRe_Gaussian_Deformation_Fields_for_Real-Time_Dynamic_Novel_View_Synthesis_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Liang_GauFRe_Gaussian_Deformation_Fields_for_Real-Time_Dynamic_Novel_View_Synthesis_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Liang_GauFRe_Gaussian_Deformation_WACV_2025_supplemental.zip | 2312.11458 | cvf | @InProceedings{Liang_2025_WACV,
author = {Liang, Yiqing and Khan, Numair and Li, Zhengqin and Nguyen-Phuoc, Thu H and Lanman, Douglas and Tompkin, James and Xiao, Lei},
title = {GauFRe: Gaussian Deformation Fields for Real-Time Dynamic Novel View Synthesis},
booktitle = {Proceedings of the Winter Con... | We propose a method that achieves state-of-the-art rendering quality and efficiency on monocular dynamic scene reconstruction using deformable 3D Gaussians. Implicit deformable representations commonly model motion with a canonical space and time-dependent backward-warping deformation field. Our method GauFRe uses a fo... |
Xie_AC-IND_Sparse_CT_Reconstruction_Based_on_Attenuation_Coefficient_Estimation_and_WACV_2025_paper | AC-IND: Sparse CT Reconstruction Based on Attenuation Coefficient Estimation and Implicit Neural Distribution | [
"Wangduo Xie",
"Richard Schoonhoven",
"Tristan van Leeuwen",
"Matthew B. Blaschko"
] | https://openaccess.thecvf.com/content/WACV2025/html/Xie_AC-IND_Sparse_CT_Reconstruction_Based_on_Attenuation_Coefficient_Estimation_and_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Xie_AC-IND_Sparse_CT_Reconstruction_Based_on_Attenuation_Coefficient_Estimation_and_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Xie_AC-IND_Sparse_CT_WACV_2025_supplemental.pdf | 2409.07171 | title_snapshot | @InProceedings{Xie_2025_WACV,
author = {Xie, Wangduo and Schoonhoven, Richard and van Leeuwen, Tristan and Blaschko, Matthew B.},
title = {AC-IND: Sparse CT Reconstruction Based on Attenuation Coefficient Estimation and Implicit Neural Distribution},
booktitle = {Proceedings of the Winter Conference ... | Computed tomography (CT) reconstruction plays a crucial role in industrial nondestructive testing and medical diagnosis. Sparse view CT reconstruction aims to reconstruct high-quality CT images while only using a small number of projections which helps to improve the detection speed of industrial assembly lines and is ... |
Gu_ORID_Organ-Regional_Information_Driven_Framework_for_Radiology_Report_Generation_WACV_2025_paper | ORID: Organ-Regional Information Driven Framework for Radiology Report Generation | [
"Tiancheng Gu",
"Kaicheng Yang",
"Xiang An",
"Ziyong Feng",
"Dongnan Liu",
"Weidong Cai"
] | https://openaccess.thecvf.com/content/WACV2025/html/Gu_ORID_Organ-Regional_Information_Driven_Framework_for_Radiology_Report_Generation_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Gu_ORID_Organ-Regional_Information_Driven_Framework_for_Radiology_Report_Generation_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Gu_ORID_Organ-Regional_Information_WACV_2025_supplemental.pdf | 2411.13025 | cvf | @InProceedings{Gu_2025_WACV,
author = {Gu, Tiancheng and Yang, Kaicheng and An, Xiang and Feng, Ziyong and Liu, Dongnan and Cai, Weidong},
title = {ORID: Organ-Regional Information Driven Framework for Radiology Report Generation},
booktitle = {Proceedings of the Winter Conference on Applications of ... | The objective of Radiology Report Generation (RRG) is to automatically generate coherent textual analyses of diseases based on radiological images thereby alleviating the workload of radiologists. Current AI-based methods for RRG primarily focus on modifications to the encoder-decoder model architecture. To advance the... |
Rai_Rubric-Constrained_Figure_Skating_Scoring_WACV_2025_paper | Rubric-Constrained Figure Skating Scoring | [
"Arushi Rai",
"Adriana Kovashka"
] | https://openaccess.thecvf.com/content/WACV2025/html/Rai_Rubric-Constrained_Figure_Skating_Scoring_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Rai_Rubric-Constrained_Figure_Skating_Scoring_WACV_2025_paper.pdf | null | null | null | @InProceedings{Rai_2025_WACV,
author = {Rai, Arushi and Kovashka, Adriana},
title = {Rubric-Constrained Figure Skating Scoring},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {February},
year = {2025},
pages = {9087-9095... | Figure skating automatic scoring is the task of estimating the competition score of a performance video. The technical element score (TES) aggregates the technical quality (grade of execution) and difficulty (base value) scores for each element. Most prior work adapted from short-term action quality assessment entangle... |
Feillet_A_Reality_Check_on_Pre-training_for_Exemplar-free_Class-Incremental_Learning_WACV_2025_paper | A Reality Check on Pre-training for Exemplar-free Class-Incremental Learning | [
"Eva Feillet",
"Adrian Popescu",
"Céline Hudelot"
] | https://openaccess.thecvf.com/content/WACV2025/html/Feillet_A_Reality_Check_on_Pre-training_for_Exemplar-free_Class-Incremental_Learning_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Feillet_A_Reality_Check_on_Pre-training_for_Exemplar-free_Class-Incremental_Learning_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Feillet_A_Reality_Check_WACV_2025_supplemental.pdf | null | null | @InProceedings{Feillet_2025_WACV,
author = {Feillet, Eva and Popescu, Adrian and Hudelot, C\'eline},
title = {A Reality Check on Pre-training for Exemplar-free Class-Incremental Learning},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {F... | Exemplar-free class-incremental learning (EFCIL) aims to classify streaming data without storing examples from the past. Recent EFCIL works suggest that (i) models pre-trained with large amounts of data should be used to initialize learning (ii) self-supervised learned transformers generalize better than supervised con... |
Matsumoto_Polarization_as_Texture_Microscale_3D_Shape_from_Polarized_Light_Focus_WACV_2025_paper | Polarization as Texture: Microscale 3D Shape from Polarized Light Focus | [
"Ren Matsumoto",
"Takahiro Okabe",
"Ryo Kawahara"
] | https://openaccess.thecvf.com/content/WACV2025/html/Matsumoto_Polarization_as_Texture_Microscale_3D_Shape_from_Polarized_Light_Focus_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Matsumoto_Polarization_as_Texture_Microscale_3D_Shape_from_Polarized_Light_Focus_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Matsumoto_Polarization_as_Texture_WACV_2025_supplemental.zip | null | null | @InProceedings{Matsumoto_2025_WACV,
author = {Matsumoto, Ren and Okabe, Takahiro and Kawahara, Ryo},
title = {Polarization as Texture: Microscale 3D Shape from Polarized Light Focus},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {Februa... | Defocus is a crucial cue for image-based microscale depth estimation yet its measurement depends on spatial appearance changes such as texture. We show that passively observed polarization is responsive to small irregularities of the surface visible in the microscopic world and can be leveraged for focus measure as a s... |
Huang_Fine-Grained_Controllable_Video_Generation_via_Object_Appearance_and_Context_WACV_2025_paper | Fine-Grained Controllable Video Generation via Object Appearance and Context | [
"Hsin-Ping Huang",
"Yu-Chuan Su",
"Deqing Sun",
"Lu Jiang",
"Xuhui Jia",
"Yukun Zhu",
"Ming-Hsuan Yang"
] | https://openaccess.thecvf.com/content/WACV2025/html/Huang_Fine-Grained_Controllable_Video_Generation_via_Object_Appearance_and_Context_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Huang_Fine-Grained_Controllable_Video_Generation_via_Object_Appearance_and_Context_WACV_2025_paper.pdf | null | 2312.02919 | cvf | @InProceedings{Huang_2025_WACV,
author = {Huang, Hsin-Ping and Su, Yu-Chuan and Sun, Deqing and Jiang, Lu and Jia, Xuhui and Zhu, Yukun and Yang, Ming-Hsuan},
title = {Fine-Grained Controllable Video Generation via Object Appearance and Context},
booktitle = {Proceedings of the Winter Conference on A... | While text-to-video generation shows state-of-the-art results fine-grained output control remains challenging for users relying solely on natural language prompts. In this work we present FACTOR for fine-grained controllable video generation. FACTOR provides an intuitive interface where users can manipulate the traject... |
Udayangani_Exploiting_Inter-Sample_Information_for_Long-Tailed_Out-of-Distribution_Detection_WACV_2025_paper | Exploiting Inter-Sample Information for Long-Tailed Out-of-Distribution Detection | [
"Nimeshika Udayangani",
"Hadi Mohaghegh Dolatabadi",
"Sarah Erfani",
"Christopher Leckie"
] | https://openaccess.thecvf.com/content/WACV2025/html/Udayangani_Exploiting_Inter-Sample_Information_for_Long-Tailed_Out-of-Distribution_Detection_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Udayangani_Exploiting_Inter-Sample_Information_for_Long-Tailed_Out-of-Distribution_Detection_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Udayangani_Exploiting_Inter-Sample_Information_WACV_2025_supplemental.pdf | 2511.16015 | title_snapshot | @InProceedings{Udayangani_2025_WACV,
author = {Udayangani, Nimeshika and Dolatabadi, Hadi Mohaghegh and Erfani, Sarah and Leckie, Christopher},
title = {Exploiting Inter-Sample Information for Long-Tailed Out-of-Distribution Detection},
booktitle = {Proceedings of the Winter Conference on Application... | Detecting out-of-distribution (OOD) data is essential for safe deployment of deep neural networks (DNNs). This problem becomes particularly challenging in the presence of long-tailed in-distribution (ID) datasets often leading to high false positive rates (FPR) and low tail-class ID classification accuracy. In this pap... |
Sacilotti_Transferable-Guided_Attention_is_All_You_Need_for_Video_Domain_Adaptation_WACV_2025_paper | Transferable-Guided Attention is All You Need for Video Domain Adaptation | [
"André Sacilotti",
"Samuel Felipe dos Santos",
"Nicu Sebe",
"Jurandy Almeida"
] | https://openaccess.thecvf.com/content/WACV2025/html/Sacilotti_Transferable-Guided_Attention_is_All_You_Need_for_Video_Domain_Adaptation_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Sacilotti_Transferable-Guided_Attention_is_All_You_Need_for_Video_Domain_Adaptation_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Sacilotti_Transferable-Guided_Attention_is_WACV_2025_supplemental.pdf | 2407.01375 | cvf | @InProceedings{Sacilotti_2025_WACV,
author = {Sacilotti, Andr\'e and dos Santos, Samuel Felipe and Sebe, Nicu and Almeida, Jurandy},
title = {Transferable-Guided Attention is All You Need for Video Domain Adaptation},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Visio... | Unsupervised domain adaptation (UDA) in videos is a challenging task that remains not well explored compared to image-based UDA techniques. Although vision transformers (ViT) achieve state-of-the-art performance in many computer vision tasks their use in video UDA has been little explored. Our key idea is to use transf... |
Mao_An_Encoder-Agnostic_Weakly_Supervised_Method_for_Describing_Textures_WACV_2025_paper | An Encoder-Agnostic Weakly Supervised Method for Describing Textures | [
"Shangbo Mao",
"Deepu Rajan"
] | https://openaccess.thecvf.com/content/WACV2025/html/Mao_An_Encoder-Agnostic_Weakly_Supervised_Method_for_Describing_Textures_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Mao_An_Encoder-Agnostic_Weakly_Supervised_Method_for_Describing_Textures_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Mao_An_Encoder-Agnostic_Weakly_WACV_2025_supplemental.pdf | null | null | @InProceedings{Mao_2025_WACV,
author = {Mao, Shangbo and Rajan, Deepu},
title = {An Encoder-Agnostic Weakly Supervised Method for Describing Textures},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {February},
year = {2025},
... | Recent advances in Large Language Models (LLMs) have enabled the semantic description of textures in natural language aiming to capture them in richer detail. However most methods are confined to either depending on supervised training with pairs of images and manually annotated visual attributes that most texture data... |
Das_Deciphering_the_Complaint_Aspects_Towards_an_Aspect-Based_Complaint_Identification_Model_WACV_2025_paper | Deciphering the Complaint Aspects: Towards an Aspect-Based Complaint Identification Model with Video Complaint Dataset in Finance | [
"Sarmistha Das",
"Basha Mujavarsheik",
"R E Zera Lyngkhoi",
"Sriparna Saha",
"Alka Maurya"
] | https://openaccess.thecvf.com/content/WACV2025/html/Das_Deciphering_the_Complaint_Aspects_Towards_an_Aspect-Based_Complaint_Identification_Model_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Das_Deciphering_the_Complaint_Aspects_Towards_an_Aspect-Based_Complaint_Identification_Model_WACV_2025_paper.pdf | null | 2503.00054 | title_snapshot | @InProceedings{Das_2025_WACV,
author = {Das, Sarmistha and Mujavarsheik, Basha and E Zera Lyngkhoi, R and Saha, Sriparna and Maurya, Alka},
title = {Deciphering the Complaint Aspects: Towards an Aspect-Based Complaint Identification Model with Video Complaint Dataset in Finance},
booktitle = {Proceed... | In today's competitive marketing landscape effective complaint management is crucial for customer service and business success. Video complaints integrating text and image content offer invaluable insights by addressing customer grievances and delineating product benefits and drawbacks. However comprehending nuanced co... |
Nawar_DiffuPT_Class_Imbalance_Mitigation_for_Glaucoma_Detection_via_Diffusion_Based_WACV_2025_paper | DiffuPT: Class Imbalance Mitigation for Glaucoma Detection via Diffusion Based Generation and Model Pretraining | [
"Youssof Nawar",
"Nouran Soliman",
"Moustafa Wassel",
"Mohamed ElHabebe",
"Noha Adly",
"Marwan Torki",
"Ahmed Elmassry",
"Islam Ahmed"
] | https://openaccess.thecvf.com/content/WACV2025/html/Nawar_DiffuPT_Class_Imbalance_Mitigation_for_Glaucoma_Detection_via_Diffusion_Based_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Nawar_DiffuPT_Class_Imbalance_Mitigation_for_Glaucoma_Detection_via_Diffusion_Based_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Nawar_DiffuPT_Class_Imbalance_WACV_2025_supplemental.pdf | 2412.03629 | cvf | @InProceedings{Nawar_2025_WACV,
author = {Nawar, Youssof and Soliman, Nouran and Wassel, Moustafa and ElHabebe, Mohamed and Adly, Noha and Torki, Marwan and Elmassry, Ahmed and Ahmed, Islam},
title = {DiffuPT: Class Imbalance Mitigation for Glaucoma Detection via Diffusion Based Generation and Model Pret... | Glaucoma is a progressive optic neuropathy characterized by structural damage to the optic nerve head and functional changes in the visual field. Detecting glaucoma early is crucial to preventing loss of eyesight. However medical datasets often suffer from class imbalances making detection more difficult for deep-learn... |
Chen_DiHuR_Diffusion-Guided_Generalizable_Human_Reconstruction_WACV_2025_paper | DiHuR: Diffusion-Guided Generalizable Human Reconstruction | [
"Jinnan Chen",
"Chen Li",
"Gim Hee Lee"
] | https://openaccess.thecvf.com/content/WACV2025/html/Chen_DiHuR_Diffusion-Guided_Generalizable_Human_Reconstruction_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Chen_DiHuR_Diffusion-Guided_Generalizable_Human_Reconstruction_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Chen_DiHuR_Diffusion-Guided_Generalizable_WACV_2025_supplemental.pdf | 2411.11903 | cvf | @InProceedings{Chen_2025_WACV,
author = {Chen, Jinnan and Li, Chen and Lee, Gim Hee},
title = {DiHuR: Diffusion-Guided Generalizable Human Reconstruction},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {February},
year = {2025},... | We introduce DiHuR a novel Diffusion-guided model for generalizable Human 3D Reconstruction and view synthesis from sparse minimally overlapping images. While existing generalizable human radiance fields excel at novel view synthesis they often struggle with comprehensive 3D reconstruction. Similarly directly optimizin... |
Dong_CUNSB-RFIE_Context-Aware_Unpaired_Neural_Schrodinger_Bridge_in_Retinal_Fundus_Image_WACV_2025_paper | CUNSB-RFIE: Context-Aware Unpaired Neural Schrodinger Bridge in Retinal Fundus Image Enhancement | [
"Xuanzhao Dong",
"Vamsi Krishna Vasa",
"Wenhui Zhu",
"Peijie Qiu",
"Xiwen Chen",
"Yi Su",
"Yujian Xiong",
"Zhangsihao Yang",
"Yanxi Chen",
"Yalin Wang"
] | https://openaccess.thecvf.com/content/WACV2025/html/Dong_CUNSB-RFIE_Context-Aware_Unpaired_Neural_Schrodinger_Bridge_in_Retinal_Fundus_Image_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Dong_CUNSB-RFIE_Context-Aware_Unpaired_Neural_Schrodinger_Bridge_in_Retinal_Fundus_Image_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Dong_CUNSB-RFIE_Context-Aware_Unpaired_WACV_2025_supplemental.pdf | 2409.10966 | title_snapshot | @InProceedings{Dong_2025_WACV,
author = {Dong, Xuanzhao and Vasa, Vamsi Krishna and Zhu, Wenhui and Qiu, Peijie and Chen, Xiwen and Su, Yi and Xiong, Yujian and Yang, Zhangsihao and Chen, Yanxi and Wang, Yalin},
title = {CUNSB-RFIE: Context-Aware Unpaired Neural Schrodinger Bridge in Retinal Fundus Image... | Retinal fundus photography is significant in diagnosing and monitoring retinal diseases. However systemic imperfections and operator/patient-related factors can hinder the acquisition of high-quality retinal images. Previous efforts in retinal image enhancement primarily relied on GANs which are limited by the trade-of... |
Leotescu_Self-Supervised_Incremental_Learning_of_Object_Representations_from_Arbitrary_Image_Sets_WACV_2025_paper | Self-Supervised Incremental Learning of Object Representations from Arbitrary Image Sets | [
"George Leotescu",
"Alin-Ionut Popa",
"Diana-Nicoleta N Grigore",
"Daniel Voinea",
"Pietro Perona"
] | https://openaccess.thecvf.com/content/WACV2025/html/Leotescu_Self-Supervised_Incremental_Learning_of_Object_Representations_from_Arbitrary_Image_Sets_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Leotescu_Self-Supervised_Incremental_Learning_of_Object_Representations_from_Arbitrary_Image_Sets_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Leotescu_Self-Supervised_Incremental_Learning_WACV_2025_supplemental.pdf | null | null | @InProceedings{Leotescu_2025_WACV,
author = {Leotescu, George and Popa, Alin-Ionut and Grigore, Diana-Nicoleta N and Voinea, Daniel and Perona, Pietro},
title = {Self-Supervised Incremental Learning of Object Representations from Arbitrary Image Sets},
booktitle = {Proceedings of the Winter Conferenc... | Computing a comprehensive and robust visual representation of an arbitrary object or category of objects is a complex problem. The difficulty increases when one starts from a set of uncalibrated images obtained from different sources. We propose a self-supervised approach Multi-Image Latent Embedding (MILE) which compu... |
Bacea_ECF-YOLOv7-Tiny_Improving_Feature_Fusion_and_the_Receptive_Field_for_Lightweight_WACV_2025_paper | ECF-YOLOv7-Tiny: Improving Feature Fusion and the Receptive Field for Lightweight Object Detectors | [
"Dan-Sebastian Bacea",
"Florin Oniga"
] | https://openaccess.thecvf.com/content/WACV2025/html/Bacea_ECF-YOLOv7-Tiny_Improving_Feature_Fusion_and_the_Receptive_Field_for_Lightweight_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Bacea_ECF-YOLOv7-Tiny_Improving_Feature_Fusion_and_the_Receptive_Field_for_Lightweight_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Bacea_ECF-YOLOv7-Tiny_Improving_Feature_WACV_2025_supplemental.zip | null | null | @InProceedings{Bacea_2025_WACV,
author = {Bacea, Dan-Sebastian and Oniga, Florin},
title = {ECF-YOLOv7-Tiny: Improving Feature Fusion and the Receptive Field for Lightweight Object Detectors},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month ... | In this work we aim to increase the efficiency and the detection performance of lightweight object detectors with focus on feature fusion and receptive field of the models. For improved feature fusion we introduce the Convolutional Squeeze-and-Excitation (CSE) module which requires only minimal additional computation. ... |
Wei_Breaking_the_Frame_Visual_Place_Recognition_by_Overlap_Prediction_WACV_2025_paper | Breaking the Frame: Visual Place Recognition by Overlap Prediction | [
"Tong Wei",
"Philipp Lindenberger",
"Jirí Matas",
"Daniel Barath"
] | https://openaccess.thecvf.com/content/WACV2025/html/Wei_Breaking_the_Frame_Visual_Place_Recognition_by_Overlap_Prediction_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Wei_Breaking_the_Frame_Visual_Place_Recognition_by_Overlap_Prediction_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Wei_Breaking_the_Frame_WACV_2025_supplemental.pdf | 2406.16204 | cvf | @InProceedings{Wei_2025_WACV,
author = {Wei, Tong and Lindenberger, Philipp and Matas, Jir{\'\i} and Barath, Daniel},
title = {Breaking the Frame: Visual Place Recognition by Overlap Prediction},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month ... | Visual place recognition methods struggle with occlusion and partial visual overlaps. We propose a novel visual place recognition approach based on overlap prediction called VOP shifting from traditional reliance on global image similarities and local features to image overlap prediction. VOP proceeds co-visible image ... |
Liu_Paladin_Understanding_Video_Intentions_in_Political_Advertisement_Videos_WACV_2025_paper | Paladin: Understanding Video Intentions in Political Advertisement Videos | [
"Hong Liu",
"Yuta Nakashima",
"Noboru Babaguchi"
] | https://openaccess.thecvf.com/content/WACV2025/html/Liu_Paladin_Understanding_Video_Intentions_in_Political_Advertisement_Videos_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Liu_Paladin_Understanding_Video_Intentions_in_Political_Advertisement_Videos_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Liu_Paladin_Understanding_Video_WACV_2025_supplemental.pdf | null | null | @InProceedings{Liu_2025_WACV,
author = {Liu, Hong and Nakashima, Yuta and Babaguchi, Noboru},
title = {Paladin: Understanding Video Intentions in Political Advertisement Videos},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {February},
... | In this paper we introduce a novel task for video understanding that focuses on detecting editing intentions in political advertisement videos. Political advertisement videos are edited with some intentions (e.g. "associating some candidates with negative emotions") of making people unthinkingly believe the messages in... |
Athwale_DarSwin-Unet_Distortion_Aware_Architecture_WACV_2025_paper | DarSwin-Unet: Distortion Aware Architecture | [
"Akshaya Athwale",
"Ichrak Shili",
"Émile Bergeron",
"Ola Ahmad",
"Jean-Francois Lalonde"
] | https://openaccess.thecvf.com/content/WACV2025/html/Athwale_DarSwin-Unet_Distortion_Aware_Architecture_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Athwale_DarSwin-Unet_Distortion_Aware_Architecture_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Athwale_DarSwin-Unet_Distortion_Aware_WACV_2025_supplemental.pdf | 2407.17328 | title_judge | @InProceedings{Athwale_2025_WACV,
author = {Athwale, Akshaya and Shili, Ichrak and Bergeron, \'Emile and Ahmad, Ola and Lalonde, Jean-Francois},
title = {DarSwin-Unet: Distortion Aware Architecture},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
mon... | Wide angle fisheye images are becoming increasingly common for perception tasks in applications such as robotics security and mobility (e.g. drones avionics). However current models often either ignore the distortions in wide angle images or are not suitable to perform pixel-level tasks. In this paper we present an enc... |
Luo_Transientangelo_Few-Viewpoint_Surface_Reconstruction_using_Single-Photon_Lidar_WACV_2025_paper | Transientangelo: Few-Viewpoint Surface Reconstruction using Single-Photon Lidar | [
"Weihan Luo",
"Anagh Malik",
"David B Lindell"
] | https://openaccess.thecvf.com/content/WACV2025/html/Luo_Transientangelo_Few-Viewpoint_Surface_Reconstruction_using_Single-Photon_Lidar_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Luo_Transientangelo_Few-Viewpoint_Surface_Reconstruction_using_Single-Photon_Lidar_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Luo_Transientangelo_Few-Viewpoint_Surface_WACV_2025_supplemental.pdf | 2408.12191 | cvf | @InProceedings{Luo_2025_WACV,
author = {Luo, Weihan and Malik, Anagh and Lindell, David B},
title = {Transientangelo: Few-Viewpoint Surface Reconstruction using Single-Photon Lidar},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {Februar... | We consider the problem of few-viewpoint 3D surface reconstruction using raw measurements from a lidar system. Lidar captures 3D scene geometry by emitting pulses of light to a target and recording the speed-of-light time delay of the reflected light. However conventional lidar systems do not output the raw captured wa... |
Honig_Shape-Biased_Texture_Agnostic_Representations_for_Improved_Textureless_and_Metallic_Object_WACV_2025_paper | Shape-Biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation | [
"Peter Hönig",
"Stefan Thalhammer",
"Jean-Baptiste Weibel",
"Matthias Hirschmanner",
"Markus Vincze"
] | https://openaccess.thecvf.com/content/WACV2025/html/Honig_Shape-Biased_Texture_Agnostic_Representations_for_Improved_Textureless_and_Metallic_Object_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Honig_Shape-Biased_Texture_Agnostic_Representations_for_Improved_Textureless_and_Metallic_Object_WACV_2025_paper.pdf | null | 2402.04878 | title_snapshot | @InProceedings{Honig_2025_WACV,
author = {H\"onig, Peter and Thalhammer, Stefan and Weibel, Jean-Baptiste and Hirschmanner, Matthias and Vincze, Markus},
title = {Shape-Biased Texture Agnostic Representations for Improved Textureless and Metallic Object Detection and 6D Pose Estimation},
booktitle = ... | Recent advances in machine learning have greatly benefited object detection and 6D pose estimation. However textureless and metallic objects still pose a significant challenge due to few visual cues and the texture bias of CNNs. To address this issue we propose a strategy for inducing a shape bias to CNN training. In p... |
Sun_Multi-Modal_Large_Language_Models_are_Effective_Vision_Learners_WACV_2025_paper | Multi-Modal Large Language Models are Effective Vision Learners | [
"Li Sun",
"Chaitanya Ahuja",
"Peng Chen",
"Matt D'Zmura",
"Kayhan Batmanghelich",
"Philip Bontrager"
] | https://openaccess.thecvf.com/content/WACV2025/html/Sun_Multi-Modal_Large_Language_Models_are_Effective_Vision_Learners_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Sun_Multi-Modal_Large_Language_Models_are_Effective_Vision_Learners_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Sun_Multi-Modal_Large_Language_WACV_2025_supplemental.pdf | null | null | @InProceedings{Sun_2025_WACV,
author = {Sun, Li and Ahuja, Chaitanya and Chen, Peng and D'Zmura, Matt and Batmanghelich, Kayhan and Bontrager, Philip},
title = {Multi-Modal Large Language Models are Effective Vision Learners},
booktitle = {Proceedings of the Winter Conference on Applications of Compu... | Large language models (LLMs) pre-trained on vast amounts of text have shown remarkable abilities in understanding general knowledge and commonsense. Therefore it's desirable to leverage pre-trained LLM to help solve computer vision tasks. Previous works on multi-modal LLM mainly focus on the generation capability. In t... |
Poleski_GeoGuide_Geometric_Guidance_of_Diffusion_Models_WACV_2025_paper | GeoGuide: Geometric Guidance of Diffusion Models | [
"Mateusz Poleski",
"Jacek Tabor",
"Przemyslaw Spurek"
] | https://openaccess.thecvf.com/content/WACV2025/html/Poleski_GeoGuide_Geometric_Guidance_of_Diffusion_Models_WACV_2025_paper.html | https://openaccess.thecvf.com/content/WACV2025/papers/Poleski_GeoGuide_Geometric_Guidance_of_Diffusion_Models_WACV_2025_paper.pdf | https://openaccess.thecvf.com/content/WACV2025/supplemental/Poleski_GeoGuide_Geometric_Guidance_WACV_2025_supplemental.pdf | 2407.12889 | cvf | @InProceedings{Poleski_2025_WACV,
author = {Poleski, Mateusz and Tabor, Jacek and Spurek, Przemyslaw},
title = {GeoGuide: Geometric Guidance of Diffusion Models},
booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
month = {February},
year = ... | Diffusion models are currently one of the most effective tools in image generation. This is in particular due to the fact that contrary to GANs during training they can be easily conditioned. However given a pretrained diffusion guiding it to obtain desired result is typically a more delicate task. A typical technique ... |
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