WACV
Collection
Accepted papers for WACV (IEEE/CVF Winter Conference on Applications of Computer Vision), one dataset per year. • 7 items • Updated
paper_id stringlengths 41 134 | title stringlengths 17 145 | authors listlengths 1 20 | cvf_url stringlengths 98 191 | pdf_url stringlengths 99 192 | supp_url stringlengths 102 154 ⌀ | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 3
values | bibtex large_stringlengths 326 694 | abstract large_stringlengths 621 1.99k |
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Zhang_Object-Centric_Video_Representation_for_Long-Term_Action_Anticipation_WACV_2024_paper | Object-Centric Video Representation for Long-Term Action Anticipation | [
"Ce Zhang",
"Changcheng Fu",
"Shijie Wang",
"Nakul Agarwal",
"Kwonjoon Lee",
"Chiho Choi",
"Chen Sun"
] | https://openaccess.thecvf.com/content/WACV2024/html/Zhang_Object-Centric_Video_Representation_for_Long-Term_Action_Anticipation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Zhang_Object-Centric_Video_Representation_for_Long-Term_Action_Anticipation_WACV_2024_paper.pdf | null | 2311.00180 | cvf | @InProceedings{Zhang_2024_WACV,
author = {Zhang, Ce and Fu, Changcheng and Wang, Shijie and Agarwal, Nakul and Lee, Kwonjoon and Choi, Chiho and Sun, Chen},
title = {Object-Centric Video Representation for Long-Term Action Anticipation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on A... | This paper focuses on building object-centric representations for long-term action anticipation in videos. Our key motivation is that objects provide important cues to recognize and predict human-object interactions, especially when the predictions are longer term, as an observed "background" object could be used by th... |
Honda_CLRerNet_Improving_Confidence_of_Lane_Detection_With_LaneIoU_WACV_2024_paper | CLRerNet: Improving Confidence of Lane Detection With LaneIoU | [
"Hiroto Honda",
"Yusuke Uchida"
] | https://openaccess.thecvf.com/content/WACV2024/html/Honda_CLRerNet_Improving_Confidence_of_Lane_Detection_With_LaneIoU_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Honda_CLRerNet_Improving_Confidence_of_Lane_Detection_With_LaneIoU_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Honda_CLRerNet_Improving_Confidence_WACV_2024_supplemental.pdf | 2305.08366 | cvf | @InProceedings{Honda_2024_WACV,
author = {Honda, Hiroto and Uchida, Yusuke},
title = {CLRerNet: Improving Confidence of Lane Detection With LaneIoU},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2024... | Lane marker detection is a crucial component of the autonomous driving and driver assistance systems. Modern deep lane detection methods with anchor-based lane representation exhibit excellent performance on lane detection benchmarks. Through preliminary oracle experiments, we firstly disentangle the lane representatio... |
Stojnic_Training_Ensembles_With_Inliers_and_Outliers_for_Semi-Supervised_Active_Learning_WACV_2024_paper | Training Ensembles With Inliers and Outliers for Semi-Supervised Active Learning | [
"Vladan Stojnić",
"Zakaria Laskar",
"Giorgos Tolias"
] | https://openaccess.thecvf.com/content/WACV2024/html/Stojnic_Training_Ensembles_With_Inliers_and_Outliers_for_Semi-Supervised_Active_Learning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Stojnic_Training_Ensembles_With_Inliers_and_Outliers_for_Semi-Supervised_Active_Learning_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Stojnic_Training_Ensembles_With_WACV_2024_supplemental.pdf | 2307.03741 | title_snapshot | @InProceedings{Stojnic_2024_WACV,
author = {Stojni\'c, Vladan and Laskar, Zakaria and Tolias, Giorgos},
title = {Training Ensembles With Inliers and Outliers for Semi-Supervised Active Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Deep active learning in the presence of outlier examples poses a realistic yet challenging scenario. Acquiring unlabeled data for annotation requires a delicate balance between avoiding outliers to conserve the annotation budget and prioritizing useful inlier examples for effective training. In this work, we present an... |
Li_Robust_Source-Free_Domain_Adaptation_for_Fundus_Image_Segmentation_WACV_2024_paper | Robust Source-Free Domain Adaptation for Fundus Image Segmentation | [
"Lingrui Li",
"Yanfeng Zhou",
"Ge Yang"
] | https://openaccess.thecvf.com/content/WACV2024/html/Li_Robust_Source-Free_Domain_Adaptation_for_Fundus_Image_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Li_Robust_Source-Free_Domain_Adaptation_for_Fundus_Image_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Li_Robust_Source-Free_Domain_WACV_2024_supplemental.pdf | 2310.16665 | cvf | @InProceedings{Li_2024_WACV,
author = {Li, Lingrui and Zhou, Yanfeng and Yang, Ge},
title = {Robust Source-Free Domain Adaptation for Fundus Image Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Unsupervised Domain Adaptation (UDA) is a learning technique that transfers knowledge learned in the source domain from labelled training data to the target domain with only unlabelled data. It is of significant importance to medical image segmentation because of the usual lack of labelled training data. Although exten... |
Iwai_Controlling_Rate_Distortion_and_Realism_Towards_a_Single_Comprehensive_Neural_WACV_2024_paper | Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Model | [
"Shoma Iwai",
"Tomo Miyazaki",
"Shinichiro Omachi"
] | https://openaccess.thecvf.com/content/WACV2024/html/Iwai_Controlling_Rate_Distortion_and_Realism_Towards_a_Single_Comprehensive_Neural_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Iwai_Controlling_Rate_Distortion_and_Realism_Towards_a_Single_Comprehensive_Neural_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Iwai_Controlling_Rate_Distortion_WACV_2024_supplemental.pdf | 2405.16817 | title_snapshot | @InProceedings{Iwai_2024_WACV,
author = {Iwai, Shoma and Miyazaki, Tomo and Omachi, Shinichiro},
title = {Controlling Rate, Distortion, and Realism: Towards a Single Comprehensive Neural Image Compression Model},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer V... | In recent years, neural network-driven image compression (NIC) has gained significant attention. Some works adopt deep generative models such as GANs and diffusion models to enhance perceptual quality (realism). A critical obstacle of these generative NIC methods is that each model is optimized for a single bit rate. C... |
Lim_MetaVers_Meta-Learned_Versatile_Representations_for_Personalized_Federated_Learning_WACV_2024_paper | MetaVers: Meta-Learned Versatile Representations for Personalized Federated Learning | [
"Jin Hyuk Lim",
"SeungBum Ha",
"Sung Whan Yoon"
] | https://openaccess.thecvf.com/content/WACV2024/html/Lim_MetaVers_Meta-Learned_Versatile_Representations_for_Personalized_Federated_Learning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Lim_MetaVers_Meta-Learned_Versatile_Representations_for_Personalized_Federated_Learning_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Lim_MetaVers_Meta-Learned_Versatile_WACV_2024_supplemental.pdf | null | null | @InProceedings{Lim_2024_WACV,
author = {Lim, Jin Hyuk and Ha, SeungBum and Yoon, Sung Whan},
title = {MetaVers: Meta-Learned Versatile Representations for Personalized Federated Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | One of the daunting challenges in federated learning (FL) is the heterogeneity across clients that hinders the successful federation of a global model. When the heterogeneity becomes worse, personalized federated learning (PFL) pursues to detour the hardship of capturing the commonality across clients by allowing the p... |
Wallin_Improving_Open-Set_Semi-Supervised_Learning_With_Self-Supervision_WACV_2024_paper | Improving Open-Set Semi-Supervised Learning With Self-Supervision | [
"Erik Wallin",
"Lennart Svensson",
"Fredrik Kahl",
"Lars Hammarstrand"
] | https://openaccess.thecvf.com/content/WACV2024/html/Wallin_Improving_Open-Set_Semi-Supervised_Learning_With_Self-Supervision_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Wallin_Improving_Open-Set_Semi-Supervised_Learning_With_Self-Supervision_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Wallin_Improving_Open-Set_Semi-Supervised_WACV_2024_supplemental.pdf | 2301.10127 | cvf | @InProceedings{Wallin_2024_WACV,
author = {Wallin, Erik and Svensson, Lennart and Kahl, Fredrik and Hammarstrand, Lars},
title = {Improving Open-Set Semi-Supervised Learning With Self-Supervision},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Open-set semi-supervised learning (OSSL) embodies a practical scenario within semi-supervised learning, wherein the unlabeled training set encompasses classes absent from the labeled set. Many existing OSSL methods assume that these out-of-distribution data are harmful and put effort into excluding data belonging to un... |
Barsellotti_FOSSIL_Free_Open-Vocabulary_Semantic_Segmentation_Through_Synthetic_References_Retrieval_WACV_2024_paper | FOSSIL: Free Open-Vocabulary Semantic Segmentation Through Synthetic References Retrieval | [
"Luca Barsellotti",
"Roberto Amoroso",
"Lorenzo Baraldi",
"Rita Cucchiara"
] | https://openaccess.thecvf.com/content/WACV2024/html/Barsellotti_FOSSIL_Free_Open-Vocabulary_Semantic_Segmentation_Through_Synthetic_References_Retrieval_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Barsellotti_FOSSIL_Free_Open-Vocabulary_Semantic_Segmentation_Through_Synthetic_References_Retrieval_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Barsellotti_FOSSIL_Free_Open-Vocabulary_WACV_2024_supplemental.pdf | null | null | @InProceedings{Barsellotti_2024_WACV,
author = {Barsellotti, Luca and Amoroso, Roberto and Baraldi, Lorenzo and Cucchiara, Rita},
title = {FOSSIL: Free Open-Vocabulary Semantic Segmentation Through Synthetic References Retrieval},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicat... | Unsupervised Open-Vocabulary Semantic Segmentation aims to segment an image into regions referring to an arbitrary set of concepts described by text, without relying on dense annotations that are available only for a subset of the categories. Previous works relied on inducing pixel-level alignment in a multi-modal spac... |
Rani_Activity-Based_Early_Autism_Diagnosis_Using_a_Multi-Dataset_Supervised_Contrastive_Learning_WACV_2024_paper | Activity-Based Early Autism Diagnosis Using a Multi-Dataset Supervised Contrastive Learning Approach | [
"Asha Rani",
"Yashaswi Verma"
] | https://openaccess.thecvf.com/content/WACV2024/html/Rani_Activity-Based_Early_Autism_Diagnosis_Using_a_Multi-Dataset_Supervised_Contrastive_Learning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Rani_Activity-Based_Early_Autism_Diagnosis_Using_a_Multi-Dataset_Supervised_Contrastive_Learning_WACV_2024_paper.pdf | null | 2209.05379 | title_judge | @InProceedings{Rani_2024_WACV,
author = {Rani, Asha and Verma, Yashaswi},
title = {Activity-Based Early Autism Diagnosis Using a Multi-Dataset Supervised Contrastive Learning Approach},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Autism Spectrum Disorder (ASD) is a neurological disorder. Its primary symptoms include difficulty in verbal/non-verbal communication and rigid/repetitive behavior. Traditional methods of autism diagnosis require multiple visits to a human specialist. However, this process is generally time-consuming and may result in ... |
Ye_Label_Shift_Estimation_for_Class-Imbalance_Problem_A_Bayesian_Approach_WACV_2024_paper | Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach | [
"Changkun Ye",
"Russell Tsuchida",
"Lars Petersson",
"Nick Barnes"
] | https://openaccess.thecvf.com/content/WACV2024/html/Ye_Label_Shift_Estimation_for_Class-Imbalance_Problem_A_Bayesian_Approach_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Ye_Label_Shift_Estimation_for_Class-Imbalance_Problem_A_Bayesian_Approach_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Ye_Label_Shift_Estimation_WACV_2024_supplemental.pdf | null | null | @InProceedings{Ye_2024_WACV,
author = {Ye, Changkun and Tsuchida, Russell and Petersson, Lars and Barnes, Nick},
title = {Label Shift Estimation for Class-Imbalance Problem: A Bayesian Approach},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | As a type of distribution shift, label shift occurs when the source and target domains have different label distributions P(Y) but identical conditional distributions of data given labels P(X | Y). Under a Bayesian framework, we propose a novel Maximum A Posteriori (MAP) model and a novel posterior sampling model for t... |
Adam_SeaTurtleID2022_A_Long-Span_Dataset_for_Reliable_Sea_Turtle_Re-Identification_WACV_2024_paper | SeaTurtleID2022: A Long-Span Dataset for Reliable Sea Turtle Re-Identification | [
"Lukáš Adam",
"Vojtěch Čermák",
"Kostas Papafitsoros",
"Lukas Picek"
] | https://openaccess.thecvf.com/content/WACV2024/html/Adam_SeaTurtleID2022_A_Long-Span_Dataset_for_Reliable_Sea_Turtle_Re-Identification_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Adam_SeaTurtleID2022_A_Long-Span_Dataset_for_Reliable_Sea_Turtle_Re-Identification_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Adam_SeaTurtleID2022_A_Long-Span_WACV_2024_supplemental.pdf | 2211.10307 | title_snapshot | @InProceedings{Adam_2024_WACV,
author = {Adam, Luk\'a\v{s} and \v{C}erm\'ak, Vojt\v{e}ch and Papafitsoros, Kostas and Picek, Lukas},
title = {SeaTurtleID2022: A Long-Span Dataset for Reliable Sea Turtle Re-Identification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of ... | This paper introduces the first public large-scale, long-span dataset with sea turtle photographs captured in the wild - SeaTurtleID2022. The dataset contains 8729 photographs of 438 unique individuals collected within 13 years, making it the longest-spanned dataset for animal re-identification. Each photograph include... |
Xu_Self-Supervised_Edge_Detection_Reconstruction_for_Topology-Informed_3D_Axon_Segmentation_and_WACV_2024_paper | Self-Supervised Edge Detection Reconstruction for Topology-Informed 3D Axon Segmentation and Centerline Detection | [
"Alec S. Xu",
"Nina I. Shamsi",
"Lars A. Gjesteby",
"Laura J. Brattain"
] | https://openaccess.thecvf.com/content/WACV2024/html/Xu_Self-Supervised_Edge_Detection_Reconstruction_for_Topology-Informed_3D_Axon_Segmentation_and_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Xu_Self-Supervised_Edge_Detection_Reconstruction_for_Topology-Informed_3D_Axon_Segmentation_and_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Xu_Self-Supervised_Edge_Detection_WACV_2024_supplemental.zip | null | null | @InProceedings{Xu_2024_WACV,
author = {Xu, Alec S. and Shamsi, Nina I. and Gjesteby, Lars A. and Brattain, Laura J.},
title = {Self-Supervised Edge Detection Reconstruction for Topology-Informed 3D Axon Segmentation and Centerline Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference... | Many machine learning-based axon tracing methods rely on image datasets with segmentation labels. This requires manual annotation from domain experts, which is labor-intensive and not practical for large-scale brain mapping on hemisphere or whole brain tissue at cellular or sub-cellular resolution. Additionally, preser... |
Liu_Bi-Directional_Training_for_Composed_Image_Retrieval_via_Text_Prompt_Learning_WACV_2024_paper | Bi-Directional Training for Composed Image Retrieval via Text Prompt Learning | [
"Zheyuan Liu",
"Weixuan Sun",
"Yicong Hong",
"Damien Teney",
"Stephen Gould"
] | https://openaccess.thecvf.com/content/WACV2024/html/Liu_Bi-Directional_Training_for_Composed_Image_Retrieval_via_Text_Prompt_Learning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Liu_Bi-Directional_Training_for_Composed_Image_Retrieval_via_Text_Prompt_Learning_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Liu_Bi-Directional_Training_for_WACV_2024_supplemental.pdf | 2303.16604 | cvf | @InProceedings{Liu_2024_WACV,
author = {Liu, Zheyuan and Sun, Weixuan and Hong, Yicong and Teney, Damien and Gould, Stephen},
title = {Bi-Directional Training for Composed Image Retrieval via Text Prompt Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer... | Composed image retrieval searches for a target image based on a multi-modal user query comprised of a reference image and modification text describing the desired changes. Existing approaches to solving this challenging task learn a mapping from the (reference image, modification text)-pair to an image embedding that i... |
Jing_iBARLE_imBalance-Aware_Room_Layout_Estimation_WACV_2024_paper | iBARLE: imBalance-Aware Room Layout Estimation | [
"Taotao Jing",
"Lichen Wang",
"Naji Khosravan",
"Zhiqiang Wan",
"Zachary Bessinger",
"Zhengming Ding",
"Sing Bing Kang"
] | https://openaccess.thecvf.com/content/WACV2024/html/Jing_iBARLE_imBalance-Aware_Room_Layout_Estimation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Jing_iBARLE_imBalance-Aware_Room_Layout_Estimation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Jing_iBARLE_imBalance-Aware_Room_WACV_2024_supplemental.pdf | 2308.15050 | cvf | @InProceedings{Jing_2024_WACV,
author = {Jing, Taotao and Wang, Lichen and Khosravan, Naji and Wan, Zhiqiang and Bessinger, Zachary and Ding, Zhengming and Kang, Sing Bing},
title = {iBARLE: imBalance-Aware Room Layout Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applica... | Room layout estimation predicts layouts from a single panorama. It requires datasets with large-scale and diverse room shapes to well train the models. However, there are significant imbalances in real-world datasets including the dimensions of layout complexity, camera locations, and variation in scene appearance. The... |
Liu_FarSight_A_Physics-Driven_Whole-Body_Biometric_System_at_Large_Distance_and_WACV_2024_paper | FarSight: A Physics-Driven Whole-Body Biometric System at Large Distance and Altitude | [
"Feng Liu",
"Ryan Ashbaugh",
"Nicholas Chimitt",
"Najmul Hassan",
"Ali Hassani",
"Ajay Jaiswal",
"Minchul Kim",
"Zhiyuan Mao",
"Christopher Perry",
"Zhiyuan Ren",
"Yiyang Su",
"Pegah Varghaei",
"Kai Wang",
"Xingguang Zhang",
"Stanley Chan",
"Arun Ross",
"Humphrey Shi",
"Zhangyang W... | https://openaccess.thecvf.com/content/WACV2024/html/Liu_FarSight_A_Physics-Driven_Whole-Body_Biometric_System_at_Large_Distance_and_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Liu_FarSight_A_Physics-Driven_Whole-Body_Biometric_System_at_Large_Distance_and_WACV_2024_paper.pdf | null | 2306.17206 | cvf | @InProceedings{Liu_2024_WACV,
author = {Liu, Feng and Ashbaugh, Ryan and Chimitt, Nicholas and Hassan, Najmul and Hassani, Ali and Jaiswal, Ajay and Kim, Minchul and Mao, Zhiyuan and Perry, Christopher and Ren, Zhiyuan and Su, Yiyang and Varghaei, Pegah and Wang, Kai and Zhang, Xingguang and Chan, Stanley and Ro... | Whole-body biometric recognition is an important area of research due to its vast applications in law enforcement, border security, and surveillance. This paper presents the end-to-end design, development and evaluation of FarSight, an innovative software system designed for whole-body (fusion of face, gait and body sh... |
Rothmeier_Time_To_Shine_Fine-Tuning_Object_Detection_Models_With_Synthetic_Adverse_WACV_2024_paper | Time To Shine: Fine-Tuning Object Detection Models With Synthetic Adverse Weather Images | [
"Thomas Rothmeier",
"Werner Huber",
"Alois C. Knoll"
] | https://openaccess.thecvf.com/content/WACV2024/html/Rothmeier_Time_To_Shine_Fine-Tuning_Object_Detection_Models_With_Synthetic_Adverse_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Rothmeier_Time_To_Shine_Fine-Tuning_Object_Detection_Models_With_Synthetic_Adverse_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Rothmeier_Time_To_Shine_WACV_2024_supplemental.pdf | null | null | @InProceedings{Rothmeier_2024_WACV,
author = {Rothmeier, Thomas and Huber, Werner and Knoll, Alois C.},
title = {Time To Shine: Fine-Tuning Object Detection Models With Synthetic Adverse Weather Images},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WA... | The detection of vehicles, pedestrians, and obstacles plays an important role in the decision-making process of autonomous vehicles. While existing methods achieve high detection accuracy under good environmental conditions, they often fail in adverse weather conditions due to limited visibility, blurred contours, and ... |
Chakraborty_Unsupervised_and_Semi-Supervised_Co-Salient_Object_Detection_via_Segmentation_Frequency_Statistics_WACV_2024_paper | Unsupervised and Semi-Supervised Co-Salient Object Detection via Segmentation Frequency Statistics | [
"Souradeep Chakraborty",
"Shujon Naha",
"Muhammet Bastan",
"Amit Kumar K. C.",
"Dimitris Samaras"
] | https://openaccess.thecvf.com/content/WACV2024/html/Chakraborty_Unsupervised_and_Semi-Supervised_Co-Salient_Object_Detection_via_Segmentation_Frequency_Statistics_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Chakraborty_Unsupervised_and_Semi-Supervised_Co-Salient_Object_Detection_via_Segmentation_Frequency_Statistics_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Chakraborty_Unsupervised_and_Semi-Supervised_WACV_2024_supplemental.pdf | 2311.06654 | cvf | @InProceedings{Chakraborty_2024_WACV,
author = {Chakraborty, Souradeep and Naha, Shujon and Bastan, Muhammet and C., Amit Kumar K. and Samaras, Dimitris},
title = {Unsupervised and Semi-Supervised Co-Salient Object Detection via Segmentation Frequency Statistics},
booktitle = {Proceedings of the IEEE... | In this paper, we address the detection of co-occurring salient objects (CoSOD) in an image group using frequency statistics in an unsupervised manner, which further enable us to develop a semi-supervised method. While previous works have mostly focused on fully supervised CoSOD, less attention has been allocated to de... |
Yasarla_3SD_Self-Supervised_Saliency_Detection_With_No_Labels_WACV_2024_paper | 3SD: Self-Supervised Saliency Detection With No Labels | [
"Rajeev Yasarla",
"Renliang Weng",
"Wongun Choi",
"Vishal M. Patel",
"Amir Sadeghian"
] | https://openaccess.thecvf.com/content/WACV2024/html/Yasarla_3SD_Self-Supervised_Saliency_Detection_With_No_Labels_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Yasarla_3SD_Self-Supervised_Saliency_Detection_With_No_Labels_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Yasarla_3SD_Self-Supervised_Saliency_WACV_2024_supplemental.pdf | 2203.04478 | cvf | @InProceedings{Yasarla_2024_WACV,
author = {Yasarla, Rajeev and Weng, Renliang and Choi, Wongun and Patel, Vishal M. and Sadeghian, Amir},
title = {3SD: Self-Supervised Saliency Detection With No Labels},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | We present a conceptually simple self-supervised method for saliency detection. Our method generates and uses pseudo-ground truth labels for training. The generated pseudo-GT labels don't require any kind of human annotations (e.g., pixel-wise labels or weak labels like scribbles). Recent works show that features extra... |
Chen_Pixel_Matching_Network_for_Cross-Domain_Few-Shot_Segmentation_WACV_2024_paper | Pixel Matching Network for Cross-Domain Few-Shot Segmentation | [
"Hao Chen",
"Yonghan Dong",
"Zheming Lu",
"Yunlong Yu",
"Jungong Han"
] | https://openaccess.thecvf.com/content/WACV2024/html/Chen_Pixel_Matching_Network_for_Cross-Domain_Few-Shot_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Chen_Pixel_Matching_Network_for_Cross-Domain_Few-Shot_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Chen_Pixel_Matching_Network_WACV_2024_supplemental.pdf | 2307.08434 | title_judge | @InProceedings{Chen_2024_WACV,
author = {Chen, Hao and Dong, Yonghan and Lu, Zheming and Yu, Yunlong and Han, Jungong},
title = {Pixel Matching Network for Cross-Domain Few-Shot Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
m... | Few-Shot Segmentation (FSS) aims to segment the novel class images with a few annotated samples. In the past, numerous studies have concentrated on cross-category tasks, where the training and testing sets are derived from the same dataset, while these methods face significant difficulties in domain-shift scenarios. To... |
Tan_Cross-Domain_Few-Shot_Incremental_Learning_for_Point-Cloud_Recognition_WACV_2024_paper | Cross-Domain Few-Shot Incremental Learning for Point-Cloud Recognition | [
"Yuwen Tan",
"Xiang Xiang"
] | https://openaccess.thecvf.com/content/WACV2024/html/Tan_Cross-Domain_Few-Shot_Incremental_Learning_for_Point-Cloud_Recognition_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Tan_Cross-Domain_Few-Shot_Incremental_Learning_for_Point-Cloud_Recognition_WACV_2024_paper.pdf | null | null | null | @InProceedings{Tan_2024_WACV,
author = {Tan, Yuwen and Xiang, Xiang},
title = {Cross-Domain Few-Shot Incremental Learning for Point-Cloud Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {20... | Sensing 3D objects is critical when 2D object recognition is not accessible. A robot pre-trained on a large point-cloud dataset will encounter unseen classes of 3D objects after deploying it. Therefore, the robot should be able to learn continuously in real-world scenarios. Few-shot class-incremental learning (FSCIL) r... |
Jang_Robust_Unsupervised_Domain_Adaptation_Through_Negative-View_Regularization_WACV_2024_paper | Robust Unsupervised Domain Adaptation Through Negative-View Regularization | [
"Joonhyeok Jang",
"Sunhyeok Lee",
"Seonghak Kim",
"Jung-un Kim",
"Seonghyun Kim",
"Daeshik Kim"
] | https://openaccess.thecvf.com/content/WACV2024/html/Jang_Robust_Unsupervised_Domain_Adaptation_Through_Negative-View_Regularization_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Jang_Robust_Unsupervised_Domain_Adaptation_Through_Negative-View_Regularization_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Jang_Robust_Unsupervised_Domain_WACV_2024_supplemental.pdf | null | null | @InProceedings{Jang_2024_WACV,
author = {Jang, Joonhyeok and Lee, Sunhyeok and Kim, Seonghak and Kim, Jung-un and Kim, Seonghyun and Kim, Daeshik},
title = {Robust Unsupervised Domain Adaptation Through Negative-View Regularization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Appli... | In the realm of Unsupervised Domain Adaptation (UDA), Vision Transformers (ViTs) have recently demonstrated remarkable adaptability surpassing that of traditional Convolutional Neural Networks (CNNs). Nevertheless, the patch-based structure of ViTs heavily relies on local features within image patches, potentially lead... |
Katsumata_Soft_Curriculum_for_Learning_Conditional_GANs_With_Noisy-Labeled_and_Uncurated_WACV_2024_paper | Soft Curriculum for Learning Conditional GANs With Noisy-Labeled and Uncurated Unlabeled Data | [
"Kai Katsumata",
"Duc Minh Vo",
"Tatsuya Harada",
"Hideki Nakayama"
] | https://openaccess.thecvf.com/content/WACV2024/html/Katsumata_Soft_Curriculum_for_Learning_Conditional_GANs_With_Noisy-Labeled_and_Uncurated_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Katsumata_Soft_Curriculum_for_Learning_Conditional_GANs_With_Noisy-Labeled_and_Uncurated_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Katsumata_Soft_Curriculum_for_WACV_2024_supplemental.pdf | 2307.08319 | cvf | @InProceedings{Katsumata_2024_WACV,
author = {Katsumata, Kai and Vo, Duc Minh and Harada, Tatsuya and Nakayama, Hideki},
title = {Soft Curriculum for Learning Conditional GANs With Noisy-Labeled and Uncurated Unlabeled Data},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications ... | Label-noise or curated unlabeled data are used to compensate for the assumption of clean labeled data in training the conditional generative adversarial network; however, satisfying such an extended assumption is occasionally laborious or impractical. As a step towards generative modeling accessible to everyone, we int... |
Duran_HMP_Hand_Motion_Priors_for_Pose_and_Shape_Estimation_From_WACV_2024_paper | HMP: Hand Motion Priors for Pose and Shape Estimation From Video | [
"Enes Duran",
"Muhammed Kocabas",
"Vasileios Choutas",
"Zicong Fan",
"Michael J. Black"
] | https://openaccess.thecvf.com/content/WACV2024/html/Duran_HMP_Hand_Motion_Priors_for_Pose_and_Shape_Estimation_From_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Duran_HMP_Hand_Motion_Priors_for_Pose_and_Shape_Estimation_From_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Duran_HMP_Hand_Motion_WACV_2024_supplemental.pdf | 2312.16737 | title_snapshot | @InProceedings{Duran_2024_WACV,
author = {Duran, Enes and Kocabas, Muhammed and Choutas, Vasileios and Fan, Zicong and Black, Michael J.},
title = {HMP: Hand Motion Priors for Pose and Shape Estimation From Video},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer... | Understanding how humans interact with the world necessitates accurate 3D hand pose estimation, a task complicated by the hand's high degree of articulation, frequent occlusions, self-occlusions, and rapid motions. While most existing methods rely on single-image inputs, videos have useful cues to address aforementione... |
Ao_Amodal_Intra-Class_Instance_Segmentation_Synthetic_Datasets_and_Benchmark_WACV_2024_paper | Amodal Intra-Class Instance Segmentation: Synthetic Datasets and Benchmark | [
"Jiayang Ao",
"Qiuhong Ke",
"Krista A. Ehinger"
] | https://openaccess.thecvf.com/content/WACV2024/html/Ao_Amodal_Intra-Class_Instance_Segmentation_Synthetic_Datasets_and_Benchmark_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Ao_Amodal_Intra-Class_Instance_Segmentation_Synthetic_Datasets_and_Benchmark_WACV_2024_paper.pdf | null | 2303.06596 | cvf | @InProceedings{Ao_2024_WACV,
author = {Ao, Jiayang and Ke, Qiuhong and Ehinger, Krista A.},
title = {Amodal Intra-Class Instance Segmentation: Synthetic Datasets and Benchmark},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Jan... | Images of realistic scenes often contain intra-class objects that are heavily occluded from each other, making the amodal perception task that requires parsing the occluded parts of the objects challenging. Although important for downstream tasks such as robotic grasping systems, the lack of large-scale amodal datasets... |
Cho_RMFER_Semi-Supervised_Contrastive_Learning_for_Facial_Expression_Recognition_With_Reaction_WACV_2024_paper | RMFER: Semi-Supervised Contrastive Learning for Facial Expression Recognition With Reaction Mashup Video | [
"Yunseong Cho",
"Chanwoo Kim",
"Hoseong Cho",
"Yunhoe Ku",
"Eunseo Kim",
"Muhammadjon Boboev",
"Joonseok Lee",
"Seungryul Baek"
] | https://openaccess.thecvf.com/content/WACV2024/html/Cho_RMFER_Semi-Supervised_Contrastive_Learning_for_Facial_Expression_Recognition_With_Reaction_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Cho_RMFER_Semi-Supervised_Contrastive_Learning_for_Facial_Expression_Recognition_With_Reaction_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Cho_RMFER_Semi-Supervised_Contrastive_WACV_2024_supplemental.pdf | null | null | @InProceedings{Cho_2024_WACV,
author = {Cho, Yunseong and Kim, Chanwoo and Cho, Hoseong and Ku, Yunhoe and Kim, Eunseo and Boboev, Muhammadjon and Lee, Joonseok and Baek, Seungryul},
title = {RMFER: Semi-Supervised Contrastive Learning for Facial Expression Recognition With Reaction Mashup Video},
bo... | Facial expression recognition (FER) has greatly benefited from deep learning but still faces challenges in dataset collection due to the nuanced nature of facial expressions. In this study, we present a novel unlabeled dataset and semi-supervised contrastive learning framework that utilizes Reaction Mashup (RM) videos,... |
Banerjee_AMEND_Adaptive_Margin_and_Expanded_Neighborhood_for_Efficient_Generalized_Category_WACV_2024_paper | AMEND: Adaptive Margin and Expanded Neighborhood for Efficient Generalized Category Discovery | [
"Anwesha Banerjee",
"Liyana Sahir Kallooriyakath",
"Soma Biswas"
] | https://openaccess.thecvf.com/content/WACV2024/html/Banerjee_AMEND_Adaptive_Margin_and_Expanded_Neighborhood_for_Efficient_Generalized_Category_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Banerjee_AMEND_Adaptive_Margin_and_Expanded_Neighborhood_for_Efficient_Generalized_Category_WACV_2024_paper.pdf | null | null | null | @InProceedings{Banerjee_2024_WACV,
author = {Banerjee, Anwesha and Kallooriyakath, Liyana Sahir and Biswas, Soma},
title = {AMEND: Adaptive Margin and Expanded Neighborhood for Efficient Generalized Category Discovery},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Com... | Generalized Category Discovery aims to discover and cluster images from previously unseen classes, in addition to classifying images from seen classes correctly. In this work, we propose a simple, yet effective framework for this task, which not only performs on-par or better with the current approaches but is also sig... |
Siddiquee_Brainomaly_Unsupervised_Neurologic_Disease_Detection_Utilizing_Unannotated_T1-Weighted_Brain_MR_WACV_2024_paper | Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-Weighted Brain MR Images | [
"Md Mahfuzur Rahman Siddiquee",
"Jay Shah",
"Teresa Wu",
"Catherine Chong",
"Todd J. Schwedt",
"Gina Dumkrieger",
"Simona Nikolova",
"Baoxin Li"
] | https://openaccess.thecvf.com/content/WACV2024/html/Siddiquee_Brainomaly_Unsupervised_Neurologic_Disease_Detection_Utilizing_Unannotated_T1-Weighted_Brain_MR_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Siddiquee_Brainomaly_Unsupervised_Neurologic_Disease_Detection_Utilizing_Unannotated_T1-Weighted_Brain_MR_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Siddiquee_Brainomaly_Unsupervised_Neurologic_WACV_2024_supplemental.pdf | 2302.09200 | cvf | @InProceedings{Siddiquee_2024_WACV,
author = {Siddiquee, Md Mahfuzur Rahman and Shah, Jay and Wu, Teresa and Chong, Catherine and Schwedt, Todd J. and Dumkrieger, Gina and Nikolova, Simona and Li, Baoxin},
title = {Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-Weighted Br... | Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare diseases, which involve high costs, time, and effort for annotation. Unsupervised disease detection methods, such as anomaly detection, can signifi... |
De_Plaen_Contrastive_Learning_for_Multi-Object_Tracking_With_Transformers_WACV_2024_paper | Contrastive Learning for Multi-Object Tracking With Transformers | [
"Pierre-François De Plaen",
"Nicola Marinello",
"Marc Proesmans",
"Tinne Tuytelaars",
"Luc Van Gool"
] | https://openaccess.thecvf.com/content/WACV2024/html/De_Plaen_Contrastive_Learning_for_Multi-Object_Tracking_With_Transformers_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/De_Plaen_Contrastive_Learning_for_Multi-Object_Tracking_With_Transformers_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/De_Plaen_Contrastive_Learning_for_WACV_2024_supplemental.pdf | 2311.08043 | cvf | @InProceedings{De_Plaen_2024_WACV,
author = {De Plaen, Pierre-Fran\c{c}ois and Marinello, Nicola and Proesmans, Marc and Tuytelaars, Tinne and Van Gool, Luc},
title = {Contrastive Learning for Multi-Object Tracking With Transformers},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Appl... | The DEtection TRansformer (DETR) opened new possibilities for object detection by modeling it as a translation task: converting image features into object-level representations. Previous works typically add expensive modules to DETR to perform Multi-Object Tracking (MOT), resulting in more complicated architectures. We... |
Chang_BEVMap_Map-Aware_BEV_Modeling_for_3D_Perception_WACV_2024_paper | BEVMap: Map-Aware BEV Modeling for 3D Perception | [
"Mincheol Chang",
"Seokha Moon",
"Reza Mahjourian",
"Jinkyu Kim"
] | https://openaccess.thecvf.com/content/WACV2024/html/Chang_BEVMap_Map-Aware_BEV_Modeling_for_3D_Perception_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Chang_BEVMap_Map-Aware_BEV_Modeling_for_3D_Perception_WACV_2024_paper.pdf | null | null | null | @InProceedings{Chang_2024_WACV,
author = {Chang, Mincheol and Moon, Seokha and Mahjourian, Reza and Kim, Jinkyu},
title = {BEVMap: Map-Aware BEV Modeling for 3D Perception},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January... | In autonomous driving applications, there is a strong preference for modeling the world in Bird's-Eye View (BEV), as it leads to improved accuracy and performance. BEV features are widely used in perception tasks since they allow fusing information from multiple views in an efficient manner. However, BEV features gener... |
Clemmer_PreciseDebias_An_Automatic_Prompt_Engineering_Approach_for_Generative_AI_To_WACV_2024_paper | PreciseDebias: An Automatic Prompt Engineering Approach for Generative AI To Mitigate Image Demographic Biases | [
"Colton Clemmer",
"Junhua Ding",
"Yunhe Feng"
] | https://openaccess.thecvf.com/content/WACV2024/html/Clemmer_PreciseDebias_An_Automatic_Prompt_Engineering_Approach_for_Generative_AI_To_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Clemmer_PreciseDebias_An_Automatic_Prompt_Engineering_Approach_for_Generative_AI_To_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Clemmer_PreciseDebias_An_Automatic_WACV_2024_supplemental.zip | null | null | @InProceedings{Clemmer_2024_WACV,
author = {Clemmer, Colton and Ding, Junhua and Feng, Yunhe},
title = {PreciseDebias: An Automatic Prompt Engineering Approach for Generative AI To Mitigate Image Demographic Biases},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comput... | Recent years have witnessed growing concerns over demographic biases in image-centric applications, including image search engines and generative systems. While the advent of generative AI offers a pathway to mitigate these biases by producing underrepresented images, existing solutions still fail to precisely generate... |
Sarkar_Benchmark_Generation_Framework_With_Customizable_Distortions_for_Image_Classifier_Robustness_WACV_2024_paper | Benchmark Generation Framework With Customizable Distortions for Image Classifier Robustness | [
"Soumyendu Sarkar",
"Ashwin Ramesh Babu",
"Sajad Mousavi",
"Zachariah Carmichael",
"Vineet Gundecha",
"Sahand Ghorbanpour",
"Ricardo Luna Gutierrez",
"Antonio Guillen",
"Avisek Naug"
] | https://openaccess.thecvf.com/content/WACV2024/html/Sarkar_Benchmark_Generation_Framework_With_Customizable_Distortions_for_Image_Classifier_Robustness_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Sarkar_Benchmark_Generation_Framework_With_Customizable_Distortions_for_Image_Classifier_Robustness_WACV_2024_paper.pdf | null | 2310.18626 | cvf | @InProceedings{Sarkar_2024_WACV,
author = {Sarkar, Soumyendu and Babu, Ashwin Ramesh and Mousavi, Sajad and Carmichael, Zachariah and Gundecha, Vineet and Ghorbanpour, Sahand and Gutierrez, Ricardo Luna and Guillen, Antonio and Naug, Avisek},
title = {Benchmark Generation Framework With Customizable Dist... | We present a novel framework for generating adversarial benchmarks to evaluate the robustness of image classification models. The RLAB framework allows users to customize the types of distortions to be optimally applied to images, which helps address the specific distortions relevant to their deployment. The benchmark ... |
Qiu_Shape-Biased_CNNs_Are_Not_Always_Superior_in_Out-of-Distribution_Robustness_WACV_2024_paper | Shape-Biased CNNs Are Not Always Superior in Out-of-Distribution Robustness | [
"Xinkuan Qiu",
"Meina Kan",
"Yongbin Zhou",
"Yanchao Bi",
"Shiguang Shan"
] | https://openaccess.thecvf.com/content/WACV2024/html/Qiu_Shape-Biased_CNNs_Are_Not_Always_Superior_in_Out-of-Distribution_Robustness_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Qiu_Shape-Biased_CNNs_Are_Not_Always_Superior_in_Out-of-Distribution_Robustness_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Qiu_Shape-Biased_CNNs_Are_WACV_2024_supplemental.pdf | null | null | @InProceedings{Qiu_2024_WACV,
author = {Qiu, Xinkuan and Kan, Meina and Zhou, Yongbin and Bi, Yanchao and Shan, Shiguang},
title = {Shape-Biased CNNs Are Not Always Superior in Out-of-Distribution Robustness},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Visi... | In recent years, Out-of-Distribution (o.o.d) Robustness has garnered increasing attention in Deep Learning, and shape-biased Convolutional Neural Networks (CNNs) are believed to exhibit higher robustness, attributed to the inherent shape-based decision rule of human cognition. In this work, we delve deeper into the int... |
Lu_Towards_Visual_Saliency_Explanations_of_Face_Verification_WACV_2024_paper | Towards Visual Saliency Explanations of Face Verification | [
"Yuhang Lu",
"Zewei Xu",
"Touradj Ebrahimi"
] | https://openaccess.thecvf.com/content/WACV2024/html/Lu_Towards_Visual_Saliency_Explanations_of_Face_Verification_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Lu_Towards_Visual_Saliency_Explanations_of_Face_Verification_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Lu_Towards_Visual_Saliency_WACV_2024_supplemental.pdf | 2305.08546 | cvf | @InProceedings{Lu_2024_WACV,
author = {Lu, Yuhang and Xu, Zewei and Ebrahimi, Touradj},
title = {Towards Visual Saliency Explanations of Face Verification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | In the past years, deep convolutional neural networks have been pushing the frontier of face recognition (FR) techniques in both verification and identification scenarios. Despite the high accuracy, they are often criticized for lacking explainability. There has been an increasing demand for understanding the decision-... |
Huber_Bias_and_Diversity_in_Synthetic-Based_Face_Recognition_WACV_2024_paper | Bias and Diversity in Synthetic-Based Face Recognition | [
"Marco Huber",
"Anh Thi Luu",
"Fadi Boutros",
"Arjan Kuijper",
"Naser Damer"
] | https://openaccess.thecvf.com/content/WACV2024/html/Huber_Bias_and_Diversity_in_Synthetic-Based_Face_Recognition_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Huber_Bias_and_Diversity_in_Synthetic-Based_Face_Recognition_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Huber_Bias_and_Diversity_WACV_2024_supplemental.pdf | 2311.03970 | cvf | @InProceedings{Huber_2024_WACV,
author = {Huber, Marco and Luu, Anh Thi and Boutros, Fadi and Kuijper, Arjan and Damer, Naser},
title = {Bias and Diversity in Synthetic-Based Face Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Synthetic data is emerging as a substitute for authentic data to solve ethical and legal challenges in handling authentic face data. The current models can create real-looking face images of people who do not exist. However, it is a known and sensitive problem that face recognition systems are susceptible to bias, i.e.... |
Deshmukh_Textual_Alchemy_CoFormer_for_Scene_Text_Understanding_WACV_2024_paper | Textual Alchemy: CoFormer for Scene Text Understanding | [
"Gayatri Deshmukh",
"Onkar Susladkar",
"Dhruv Makwana",
"Sparsh Mittal",
"Sai Chandra Teja R."
] | https://openaccess.thecvf.com/content/WACV2024/html/Deshmukh_Textual_Alchemy_CoFormer_for_Scene_Text_Understanding_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Deshmukh_Textual_Alchemy_CoFormer_for_Scene_Text_Understanding_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Deshmukh_Textual_Alchemy_CoFormer_WACV_2024_supplemental.pdf | null | null | @InProceedings{Deshmukh_2024_WACV,
author = {Deshmukh, Gayatri and Susladkar, Onkar and Makwana, Dhruv and Mittal, Sparsh and R., Sai Chandra Teja},
title = {Textual Alchemy: CoFormer for Scene Text Understanding},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer... | The paper presents CoFormer (Convolutional Fourier Transformer), a robust and adaptable transformer architecture designed for a range of scene text tasks. CoFormer integrates convolution and Fourier operations into the transformer architecture. Thus, it leverages convolution properties such as shared weights, local rec... |
Singla_Data-Centric_Debugging_Mitigating_Model_Failures_via_Targeted_Image_Retrieval_WACV_2024_paper | Data-Centric Debugging: Mitigating Model Failures via Targeted Image Retrieval | [
"Sahil Singla",
"Atoosa Malemir Chegini",
"Mazda Moayeri",
"Soheil Feizi"
] | https://openaccess.thecvf.com/content/WACV2024/html/Singla_Data-Centric_Debugging_Mitigating_Model_Failures_via_Targeted_Image_Retrieval_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Singla_Data-Centric_Debugging_Mitigating_Model_Failures_via_Targeted_Image_Retrieval_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Singla_Data-Centric_Debugging_Mitigating_WACV_2024_supplemental.pdf | 2211.09859 | title_judge | @InProceedings{Singla_2024_WACV,
author = {Singla, Sahil and Chegini, Atoosa Malemir and Moayeri, Mazda and Feizi, Soheil},
title = {Data-Centric Debugging: Mitigating Model Failures via Targeted Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer ... | Deep neural networks can be unreliable in the real world when the training set does not adequately cover all the settings where they are deployed. Focusing on image classification, we consider the setting where we have an error distribution E representing a deployment scenario where the model fails. We have access to a... |
Fujitake_DTrOCR_Decoder-Only_Transformer_for_Optical_Character_Recognition_WACV_2024_paper | DTrOCR: Decoder-Only Transformer for Optical Character Recognition | [
"Masato Fujitake"
] | https://openaccess.thecvf.com/content/WACV2024/html/Fujitake_DTrOCR_Decoder-Only_Transformer_for_Optical_Character_Recognition_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Fujitake_DTrOCR_Decoder-Only_Transformer_for_Optical_Character_Recognition_WACV_2024_paper.pdf | null | 2308.15996 | cvf | @InProceedings{Fujitake_2024_WACV,
author = {Fujitake, Masato},
title = {DTrOCR: Decoder-Only Transformer for Optical Character Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2024},
p... | Typical text recognition methods rely on an encoder-decoder structure, in which the encoder extracts features from an image, and the decoder produces recognized text from these features. In this study, we propose a simpler and more effective method for text recognition, known as the Decoder-only Transformer for Optical... |
Wang_Efficient_Transferability_Assessment_for_Selection_of_Pre-Trained_Detectors_WACV_2024_paper | Efficient Transferability Assessment for Selection of Pre-Trained Detectors | [
"Zhao Wang",
"Aoxue Li",
"Zhenguo Li",
"Qi Dou"
] | https://openaccess.thecvf.com/content/WACV2024/html/Wang_Efficient_Transferability_Assessment_for_Selection_of_Pre-Trained_Detectors_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Wang_Efficient_Transferability_Assessment_for_Selection_of_Pre-Trained_Detectors_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Wang_Efficient_Transferability_Assessment_WACV_2024_supplemental.pdf | 2403.09432 | title_snapshot | @InProceedings{Wang_2024_WACV,
author = {Wang, Zhao and Li, Aoxue and Li, Zhenguo and Dou, Qi},
title = {Efficient Transferability Assessment for Selection of Pre-Trained Detectors},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month =... | Large-scale pre-training followed by downstream fine-tuning is an effective solution for transferring deep-learning-based models. Since finetuning all possible pre-trained models is computational costly, we aim to predict the transferability performance of these pre-trained models in a computational efficient manner. D... |
Pham_NVAutoNet_Fast_and_Accurate_360deg_3D_Visual_Perception_for_Self_WACV_2024_paper | NVAutoNet: Fast and Accurate 360deg 3D Visual Perception for Self Driving | [
"Trung Pham",
"Mehran Maghoumi",
"Wanli Jiang",
"Bala Siva Sashank Jujjavarapu",
"Mehdi Sajjadi",
"Xin Liu",
"Hsuan-Chu Lin",
"Bor-Jeng Chen",
"Giang Truong",
"Chao Fang",
"Junghyun Kwon",
"Minwoo Park"
] | https://openaccess.thecvf.com/content/WACV2024/html/Pham_NVAutoNet_Fast_and_Accurate_360deg_3D_Visual_Perception_for_Self_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Pham_NVAutoNet_Fast_and_Accurate_360deg_3D_Visual_Perception_for_Self_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Pham_NVAutoNet_Fast_and_WACV_2024_supplemental.pdf | 2303.12976 | title_judge | @InProceedings{Pham_2024_WACV,
author = {Pham, Trung and Maghoumi, Mehran and Jiang, Wanli and Jujjavarapu, Bala Siva Sashank and Sajjadi, Mehdi and Liu, Xin and Lin, Hsuan-Chu and Chen, Bor-Jeng and Truong, Giang and Fang, Chao and Kwon, Junghyun and Park, Minwoo},
title = {NVAutoNet: Fast and Accurate ... | Achieving robust and real-time 3D perception is fundamental for autonomous vehicles. While most existing 3D perception methods prioritize detection accuracy, they often overlook critical aspects such as computational efficiency, onboard chip deployment friendliness, resilience to sensor mounting deviations, and adaptab... |
Nguyen_VideoFACT_Detecting_Video_Forgeries_Using_Attention_Scene_Context_and_Forensic_WACV_2024_paper | VideoFACT: Detecting Video Forgeries Using Attention, Scene Context, and Forensic Traces | [
"Tai D. Nguyen",
"Shengbang Fang",
"Matthew C. Stamm"
] | https://openaccess.thecvf.com/content/WACV2024/html/Nguyen_VideoFACT_Detecting_Video_Forgeries_Using_Attention_Scene_Context_and_Forensic_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Nguyen_VideoFACT_Detecting_Video_Forgeries_Using_Attention_Scene_Context_and_Forensic_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Nguyen_VideoFACT_Detecting_Video_WACV_2024_supplemental.pdf | 2211.15775 | cvf | @InProceedings{Nguyen_2024_WACV,
author = {Nguyen, Tai D. and Fang, Shengbang and Stamm, Matthew C.},
title = {VideoFACT: Detecting Video Forgeries Using Attention, Scene Context, and Forensic Traces},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV... | Fake videos represent an important misinformation threat. While existing forensic networks have demonstrated strong performance on image forgeries, recent results reported on the Adobe VideoSham dataset show that these networks fail to identify fake content in videos. In response, we propose VideoFACT - a new network t... |
Vinod_TEGLO_High_Fidelity_Canonical_Texture_Mapping_From_Single-View_Images_WACV_2024_paper | TEGLO: High Fidelity Canonical Texture Mapping From Single-View Images | [
"Vishal Vinod",
"Tanmay Shah",
"Dmitry Lagun"
] | https://openaccess.thecvf.com/content/WACV2024/html/Vinod_TEGLO_High_Fidelity_Canonical_Texture_Mapping_From_Single-View_Images_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Vinod_TEGLO_High_Fidelity_Canonical_Texture_Mapping_From_Single-View_Images_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Vinod_TEGLO_High_Fidelity_WACV_2024_supplemental.zip | 2303.13743 | cvf | @InProceedings{Vinod_2024_WACV,
author = {Vinod, Vishal and Shah, Tanmay and Lagun, Dmitry},
title = {TEGLO: High Fidelity Canonical Texture Mapping From Single-View Images},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Januar... | Recent work in Neural Fields (NFs) learn 3D representations from class-specific single view image collections. However, they are unable to reconstruct the input data preserving high-frequency details. Further, these methods do not disentangle appearance from geometry and hence are not suitable for tasks such as texture... |
Nogueira_Prototypical_Contrastive_Network_for_Imbalanced_Aerial_Image_Segmentation_WACV_2024_paper | Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation | [
"Keiller Nogueira",
"Mayara Maezano Faita-Pinheiro",
"Ana Paula Marques Ramos",
"Wesley Nunes Gonçalves",
"José Marcato Junior",
"Jefersson A. dos Santos"
] | https://openaccess.thecvf.com/content/WACV2024/html/Nogueira_Prototypical_Contrastive_Network_for_Imbalanced_Aerial_Image_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Nogueira_Prototypical_Contrastive_Network_for_Imbalanced_Aerial_Image_Segmentation_WACV_2024_paper.pdf | null | null | null | @InProceedings{Nogueira_2024_WACV,
author = {Nogueira, Keiller and Faita-Pinheiro, Mayara Maezano and Ramos, Ana Paula Marques and Gon\c{c}alves, Wesley Nunes and Junior, Jos\'e Marcato and dos Santos, Jefersson A.},
title = {Prototypical Contrastive Network for Imbalanced Aerial Image Segmentation},
... | Binary segmentation is the main task underpinning several remote sensing applications, which are particularly interested in identifying and monitoring a specific category/object. Although extremely important, such a task has several challenges, including huge intra-class variance for the background and data imbalance. ... |
Haitman_BoostRad_Enhancing_Object_Detection_by_Boosting_Radar_Reflections_WACV_2024_paper | BoostRad: Enhancing Object Detection by Boosting Radar Reflections | [
"Yuval Haitman",
"Oded Bialer"
] | https://openaccess.thecvf.com/content/WACV2024/html/Haitman_BoostRad_Enhancing_Object_Detection_by_Boosting_Radar_Reflections_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Haitman_BoostRad_Enhancing_Object_Detection_by_Boosting_Radar_Reflections_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Haitman_BoostRad_Enhancing_Object_WACV_2024_supplemental.pdf | 2404.17861 | title_snapshot | @InProceedings{Haitman_2024_WACV,
author = {Haitman, Yuval and Bialer, Oded},
title = {BoostRad: Enhancing Object Detection by Boosting Radar Reflections},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year =... | Automotive radars have an important role in autonomous driving systems. The main challenge in automotive radar detection is the radar's wide point spread function (PSF) in the angular domain that causes blurriness and clutter in the radar image. Numerous studies suggest employing an 'end-to-end' learning strategy using... |
Pham_Frequency_Attention_for_Knowledge_Distillation_WACV_2024_paper | Frequency Attention for Knowledge Distillation | [
"Cuong Pham",
"Van-Anh Nguyen",
"Trung Le",
"Dinh Phung",
"Gustavo Carneiro",
"Thanh-Toan Do"
] | https://openaccess.thecvf.com/content/WACV2024/html/Pham_Frequency_Attention_for_Knowledge_Distillation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Pham_Frequency_Attention_for_Knowledge_Distillation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Pham_Frequency_Attention_for_WACV_2024_supplemental.pdf | 2403.05894 | title_snapshot | @InProceedings{Pham_2024_WACV,
author = {Pham, Cuong and Nguyen, Van-Anh and Le, Trung and Phung, Dinh and Carneiro, Gustavo and Do, Thanh-Toan},
title = {Frequency Attention for Knowledge Distillation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WA... | Knowledge distillation is an attractive approach for learning compact deep neural networks, which learns a lightweight student model by distilling knowledge from a complex teacher model. Attention-based knowledge distillation is a specific form of intermediate feature-based knowledge distillation that uses attention me... |
Jang_Lost_Your_Style_Navigating_With_Semantic-Level_Approach_for_Text-To-Outfit_Retrieval_WACV_2024_paper | Lost Your Style? Navigating With Semantic-Level Approach for Text-To-Outfit Retrieval | [
"Junkyu Jang",
"Eugene Hwang",
"Sung-Hyuk Park"
] | https://openaccess.thecvf.com/content/WACV2024/html/Jang_Lost_Your_Style_Navigating_With_Semantic-Level_Approach_for_Text-To-Outfit_Retrieval_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Jang_Lost_Your_Style_Navigating_With_Semantic-Level_Approach_for_Text-To-Outfit_Retrieval_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Jang_Lost_Your_Style_WACV_2024_supplemental.pdf | 2311.02122 | cvf | @InProceedings{Jang_2024_WACV,
author = {Jang, Junkyu and Hwang, Eugene and Park, Sung-Hyuk},
title = {Lost Your Style? Navigating With Semantic-Level Approach for Text-To-Outfit Retrieval},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mon... | Fashion stylists have historically bridged the gap between consumers' desires and perfect outfits, which involve intricate combinations of colors, patterns, and materials. Although recent advancements in fashion recommendation systems have made strides in outfit compatibility prediction and complementary item retrieval... |
Bashirov_MoRF_Mobile_Realistic_Fullbody_Avatars_From_a_Monocular_Video_WACV_2024_paper | MoRF: Mobile Realistic Fullbody Avatars From a Monocular Video | [
"Renat Bashirov",
"Alexey Larionov",
"Evgeniya Ustinova",
"Mikhail Sidorenko",
"David Svitov",
"Ilya Zakharkin",
"Victor Lempitsky"
] | https://openaccess.thecvf.com/content/WACV2024/html/Bashirov_MoRF_Mobile_Realistic_Fullbody_Avatars_From_a_Monocular_Video_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Bashirov_MoRF_Mobile_Realistic_Fullbody_Avatars_From_a_Monocular_Video_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Bashirov_MoRF_Mobile_Realistic_WACV_2024_supplemental.pdf | 2303.10275 | cvf | @InProceedings{Bashirov_2024_WACV,
author = {Bashirov, Renat and Larionov, Alexey and Ustinova, Evgeniya and Sidorenko, Mikhail and Svitov, David and Zakharkin, Ilya and Lempitsky, Victor},
title = {MoRF: Mobile Realistic Fullbody Avatars From a Monocular Video},
booktitle = {Proceedings of the IEEE/... | We present a system to create Mobile Realistic Fullbody (MoRF) avatars. MoRF avatars are rendered in real-time on mobile devices, learned from monocular videos, and have high realism. We use SMPL-X as a proxy geometry and render it with DNR (neural texture and image-2-image network). We improve on prior work, by overfi... |
Flotzinger_dacl10k_Benchmark_for_Semantic_Bridge_Damage_Segmentation_WACV_2024_paper | dacl10k: Benchmark for Semantic Bridge Damage Segmentation | [
"Johannes Flotzinger",
"Philipp J. Rösch",
"Thomas Braml"
] | https://openaccess.thecvf.com/content/WACV2024/html/Flotzinger_dacl10k_Benchmark_for_Semantic_Bridge_Damage_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Flotzinger_dacl10k_Benchmark_for_Semantic_Bridge_Damage_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Flotzinger_dacl10k_Benchmark_for_WACV_2024_supplemental.pdf | 2309.00460 | title_snapshot | @InProceedings{Flotzinger_2024_WACV,
author = {Flotzinger, Johannes and R\"osch, Philipp J. and Braml, Thomas},
title = {dacl10k: Benchmark for Semantic Bridge Damage Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = ... | Reliably identifying reinforced concrete defects (RCDs) plays a crucial role in assessing the structural integrity, traffic safety, and long-term durability of concrete bridges, which represent the most common bridge type worldwide. Nevertheless, available datasets for the recognition of RCDs are small in terms of size... |
Bernhard_Whats_Outside_the_Intersection_Fine-Grained_Error_Analysis_for_Semantic_Segmentation_WACV_2024_paper | What's Outside the Intersection? Fine-Grained Error Analysis for Semantic Segmentation Beyond IoU | [
"Maximilian Bernhard",
"Roberto Amoroso",
"Yannic Kindermann",
"Lorenzo Baraldi",
"Rita Cucchiara",
"Volker Tresp",
"Matthias Schubert"
] | https://openaccess.thecvf.com/content/WACV2024/html/Bernhard_Whats_Outside_the_Intersection_Fine-Grained_Error_Analysis_for_Semantic_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Bernhard_Whats_Outside_the_Intersection_Fine-Grained_Error_Analysis_for_Semantic_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Bernhard_Whats_Outside_the_WACV_2024_supplemental.pdf | null | null | @InProceedings{Bernhard_2024_WACV,
author = {Bernhard, Maximilian and Amoroso, Roberto and Kindermann, Yannic and Baraldi, Lorenzo and Cucchiara, Rita and Tresp, Volker and Schubert, Matthias},
title = {What's Outside the Intersection? Fine-Grained Error Analysis for Semantic Segmentation Beyond IoU},
... | Semantic segmentation represents a fundamental task in computer vision with various application areas such as autonomous driving, medical imaging, or remote sensing. For evaluating and comparing semantic segmentation models, the mean intersection over union (mIoU) is currently the gold standard. However, while mIoU ser... |
Ghaleb_Co-Speech_Gesture_Detection_Through_Multi-Phase_Sequence_Labeling_WACV_2024_paper | Co-Speech Gesture Detection Through Multi-Phase Sequence Labeling | [
"Esam Ghaleb",
"Ilya Burenko",
"Marlou Rasenberg",
"Wim Pouw",
"Peter Uhrig",
"Judith Holler",
"Ivan Toni",
"Aslı Özyürek",
"Raquel Fernández"
] | https://openaccess.thecvf.com/content/WACV2024/html/Ghaleb_Co-Speech_Gesture_Detection_Through_Multi-Phase_Sequence_Labeling_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Ghaleb_Co-Speech_Gesture_Detection_Through_Multi-Phase_Sequence_Labeling_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Ghaleb_Co-Speech_Gesture_Detection_WACV_2024_supplemental.pdf | 2308.10680 | cvf | @InProceedings{Ghaleb_2024_WACV,
author = {Ghaleb, Esam and Burenko, Ilya and Rasenberg, Marlou and Pouw, Wim and Uhrig, Peter and Holler, Judith and Toni, Ivan and \"Ozy\"urek, Asl{\i} and Fern\'andez, Raquel},
title = {Co-Speech Gesture Detection Through Multi-Phase Sequence Labeling},
booktitle = ... | Gestures are integral components of face-to-face communication. They unfold over time, often following predictable movement phases of preparation, stroke, and retraction. Yet, the prevalent approach to automatic gesture detection treats the problem as binary classification, classifying a segment as either containing a ... |
Maheshwari_Missing_Modality_Robustness_in_Semi-Supervised_Multi-Modal_Semantic_Segmentation_WACV_2024_paper | Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation | [
"Harsh Maheshwari",
"Yen-Cheng Liu",
"Zsolt Kira"
] | https://openaccess.thecvf.com/content/WACV2024/html/Maheshwari_Missing_Modality_Robustness_in_Semi-Supervised_Multi-Modal_Semantic_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Maheshwari_Missing_Modality_Robustness_in_Semi-Supervised_Multi-Modal_Semantic_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Maheshwari_Missing_Modality_Robustness_WACV_2024_supplemental.pdf | 2304.10756 | cvf | @InProceedings{Maheshwari_2024_WACV,
author = {Maheshwari, Harsh and Liu, Yen-Cheng and Kira, Zsolt},
title = {Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Using multiple spatial modalities has been proven helpful in improving semantic segmentation performance. However, there are several real-world challenges that have yet to be addressed: (a) improving label efficiency and (b) enhancing robustness in realistic scenarios where modalities are missing at the test time. To a... |
Ben-Dov_Adversarial_Likelihood_Estimation_With_One-Way_Flows_WACV_2024_paper | Adversarial Likelihood Estimation With One-Way Flows | [
"Omri Ben-Dov",
"Pravir Singh Gupta",
"Victoria Abrevaya",
"Michael J. Black",
"Partha Ghosh"
] | https://openaccess.thecvf.com/content/WACV2024/html/Ben-Dov_Adversarial_Likelihood_Estimation_With_One-Way_Flows_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Ben-Dov_Adversarial_Likelihood_Estimation_With_One-Way_Flows_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Ben-Dov_Adversarial_Likelihood_Estimation_WACV_2024_supplemental.pdf | 2307.09882 | cvf | @InProceedings{Ben-Dov_2024_WACV,
author = {Ben-Dov, Omri and Gupta, Pravir Singh and Abrevaya, Victoria and Black, Michael J. and Ghosh, Partha},
title = {Adversarial Likelihood Estimation With One-Way Flows},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vis... | Generative Adversarial Networks (GANs) can produce high-quality samples, but do not provide an estimate of the probability density around the samples. However, it has been noted that maximizing the log-likelihood within an energy-based setting can lead to an adversarial framework where the discriminator provides unnorm... |
Chang_Fast_Sun-Aligned_Outdoor_Scene_Relighting_Based_on_TensoRF_WACV_2024_paper | Fast Sun-Aligned Outdoor Scene Relighting Based on TensoRF | [
"Yeonjin Chang",
"Yearim Kim",
"Seunghyeon Seo",
"Jung Yi",
"Nojun Kwak"
] | https://openaccess.thecvf.com/content/WACV2024/html/Chang_Fast_Sun-Aligned_Outdoor_Scene_Relighting_Based_on_TensoRF_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Chang_Fast_Sun-Aligned_Outdoor_Scene_Relighting_Based_on_TensoRF_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Chang_Fast_Sun-Aligned_Outdoor_WACV_2024_supplemental.pdf | 2311.03965 | cvf | @InProceedings{Chang_2024_WACV,
author = {Chang, Yeonjin and Kim, Yearim and Seo, Seunghyeon and Yi, Jung and Kwak, Nojun},
title = {Fast Sun-Aligned Outdoor Scene Relighting Based on TensoRF},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | In this work, we introduce our method of outdoor scene relighting for Neural Radiance Fields (NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF). SR-TensoRF offers a lightweight and rapid pipeline aligned with the sun, thereby achieving a simplified workflow that eliminates the need for environment maps. Our sun-a... |
Hong_Robust_Eye_Blink_Detection_Using_Dual_Embedding_Video_Vision_Transformer_WACV_2024_paper | Robust Eye Blink Detection Using Dual Embedding Video Vision Transformer | [
"Jeongmin Hong",
"Joseph Shin",
"Juhee Choi",
"Minsam Ko"
] | https://openaccess.thecvf.com/content/WACV2024/html/Hong_Robust_Eye_Blink_Detection_Using_Dual_Embedding_Video_Vision_Transformer_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Hong_Robust_Eye_Blink_Detection_Using_Dual_Embedding_Video_Vision_Transformer_WACV_2024_paper.pdf | null | null | null | @InProceedings{Hong_2024_WACV,
author = {Hong, Jeongmin and Shin, Joseph and Choi, Juhee and Ko, Minsam},
title = {Robust Eye Blink Detection Using Dual Embedding Video Vision Transformer},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mont... | Eye blink detection serves as a crucial biomarker for evaluating both physical and mental states, garnering considerable attention in biometric and video-based studies. Among various methods, video-based eye blink detection has been particularly favored due to its non-invasive nature, enabling broader applications. How... |
Nguyen_Domain_Generalisation_via_Risk_Distribution_Matching_WACV_2024_paper | Domain Generalisation via Risk Distribution Matching | [
"Toan Nguyen",
"Kien Do",
"Bao Duong",
"Thin Nguyen"
] | https://openaccess.thecvf.com/content/WACV2024/html/Nguyen_Domain_Generalisation_via_Risk_Distribution_Matching_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Nguyen_Domain_Generalisation_via_Risk_Distribution_Matching_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Nguyen_Domain_Generalisation_via_WACV_2024_supplemental.pdf | 2310.18598 | cvf | @InProceedings{Nguyen_2024_WACV,
author = {Nguyen, Toan and Do, Kien and Duong, Bao and Nguyen, Thin},
title = {Domain Generalisation via Risk Distribution Matching},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | We propose a novel approach for domain generalisation (DG) leveraging risk distributions to characterise domains, thereby achieving domain invariance. In our findings, risk distributions effectively highlight differences between training domains and reveal their inherent complexities. In testing, we may observe similar... |
Chen_Panelformer_Sewing_Pattern_Reconstruction_From_2D_Garment_Images_WACV_2024_paper | Panelformer: Sewing Pattern Reconstruction From 2D Garment Images | [
"Cheng-Hsiu Chen",
"Jheng-Wei Su",
"Min-Chun Hu",
"Chih-Yuan Yao",
"Hung-Kuo Chu"
] | https://openaccess.thecvf.com/content/WACV2024/html/Chen_Panelformer_Sewing_Pattern_Reconstruction_From_2D_Garment_Images_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Chen_Panelformer_Sewing_Pattern_Reconstruction_From_2D_Garment_Images_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Chen_Panelformer_Sewing_Pattern_WACV_2024_supplemental.pdf | null | null | @InProceedings{Chen_2024_WACV,
author = {Chen, Cheng-Hsiu and Su, Jheng-Wei and Hu, Min-Chun and Yao, Chih-Yuan and Chu, Hung-Kuo},
title = {Panelformer: Sewing Pattern Reconstruction From 2D Garment Images},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Visio... | In this paper, we present a novel approach for reconstructing garment sewing patterns from 2D garment images. Our method addresses the challenge of handling occlusion in 2D images by leveraging the symmetric and correlated nature of garment panels. We introduce a transformer-based deep neural network called Panelformer... |
Omidi_Unsupervised_Domain_Adaptation_of_MRI_Skull-Stripping_Trained_on_Adult_Data_WACV_2024_paper | Unsupervised Domain Adaptation of MRI Skull-Stripping Trained on Adult Data to Newborns | [
"Abbas Omidi",
"Aida Mohammadshahi",
"Neha Gianchandani",
"Regan King",
"Lara Leijser",
"Roberto Souza"
] | https://openaccess.thecvf.com/content/WACV2024/html/Omidi_Unsupervised_Domain_Adaptation_of_MRI_Skull-Stripping_Trained_on_Adult_Data_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Omidi_Unsupervised_Domain_Adaptation_of_MRI_Skull-Stripping_Trained_on_Adult_Data_WACV_2024_paper.pdf | null | null | null | @InProceedings{Omidi_2024_WACV,
author = {Omidi, Abbas and Mohammadshahi, Aida and Gianchandani, Neha and King, Regan and Leijser, Lara and Souza, Roberto},
title = {Unsupervised Domain Adaptation of MRI Skull-Stripping Trained on Adult Data to Newborns},
booktitle = {Proceedings of the IEEE/CVF Wint... | Skull-stripping is an important first step when analyzing brain Magnetic Resonance Imaging (MRI) data. Deep learning-based supervised segmentation models, such as the U-net model, have shown promising results in automating this segmentation task. However, when it comes to newborn MRI data, there are no publicly availab... |
Zhang_Generated_Distributions_Are_All_You_Need_for_Membership_Inference_Attacks_WACV_2024_paper | Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models | [
"Minxing Zhang",
"Ning Yu",
"Rui Wen",
"Michael Backes",
"Yang Zhang"
] | https://openaccess.thecvf.com/content/WACV2024/html/Zhang_Generated_Distributions_Are_All_You_Need_for_Membership_Inference_Attacks_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Zhang_Generated_Distributions_Are_All_You_Need_for_Membership_Inference_Attacks_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Zhang_Generated_Distributions_Are_WACV_2024_supplemental.pdf | 2310.19410 | cvf | @InProceedings{Zhang_2024_WACV,
author = {Zhang, Minxing and Yu, Ning and Wen, Rui and Backes, Michael and Zhang, Yang},
title = {Generated Distributions Are All You Need for Membership Inference Attacks Against Generative Models},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applica... | Generative models have demonstrated revolutionary success in various visual creation tasks, but in the meantime, they have been exposed to the threat of leaking private information of their training data. Several membership inference attacks (MIAs) have been proposed to exhibit the privacy vulnerability of generative m... |
Shen_Multitask_Vision-Language_Prompt_Tuning_WACV_2024_paper | Multitask Vision-Language Prompt Tuning | [
"Sheng Shen",
"Shijia Yang",
"Tianjun Zhang",
"Bohan Zhai",
"Joseph E. Gonzalez",
"Kurt Keutzer",
"Trevor Darrell"
] | https://openaccess.thecvf.com/content/WACV2024/html/Shen_Multitask_Vision-Language_Prompt_Tuning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Shen_Multitask_Vision-Language_Prompt_Tuning_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Shen_Multitask_Vision-Language_Prompt_WACV_2024_supplemental.pdf | 2211.11720 | cvf | @InProceedings{Shen_2024_WACV,
author = {Shen, Sheng and Yang, Shijia and Zhang, Tianjun and Zhai, Bohan and Gonzalez, Joseph E. and Keutzer, Kurt and Darrell, Trevor},
title = {Multitask Vision-Language Prompt Tuning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Com... | Prompt Tuning, conditioning on task-specific learned prompt vectors, has emerged as a data-efficient and parameter-efficient method for adapting large pretrained vision-language models to multiple downstream tasks. However, existing approaches usually consider learning prompt vectors for each task independently from sc... |
Barbany_ProcSim_Proxy-Based_Confidence_for_Robust_Similarity_Learning_WACV_2024_paper | ProcSim: Proxy-Based Confidence for Robust Similarity Learning | [
"Oriol Barbany",
"Xiaofan Lin",
"Muhammet Bastan",
"Arnab Dhua"
] | https://openaccess.thecvf.com/content/WACV2024/html/Barbany_ProcSim_Proxy-Based_Confidence_for_Robust_Similarity_Learning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Barbany_ProcSim_Proxy-Based_Confidence_for_Robust_Similarity_Learning_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Barbany_ProcSim_Proxy-Based_Confidence_WACV_2024_supplemental.pdf | 2311.00668 | cvf | @InProceedings{Barbany_2024_WACV,
author = {Barbany, Oriol and Lin, Xiaofan and Bastan, Muhammet and Dhua, Arnab},
title = {ProcSim: Proxy-Based Confidence for Robust Similarity Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | Deep Metric Learning (DML) methods aim at learning an embedding space in which distances are closely related to the inherent semantic similarity of the inputs. Previous studies have shown that popular benchmark datasets often contain numerous wrong labels, and DML methods are susceptible to them. Intending to study the... |
Park_Hard-Label_Based_Small_Query_Black-Box_Adversarial_Attack_WACV_2024_paper | Hard-Label Based Small Query Black-Box Adversarial Attack | [
"Jeonghwan Park",
"Paul Miller",
"Niall McLaughlin"
] | https://openaccess.thecvf.com/content/WACV2024/html/Park_Hard-Label_Based_Small_Query_Black-Box_Adversarial_Attack_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Park_Hard-Label_Based_Small_Query_Black-Box_Adversarial_Attack_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Park_Hard-Label_Based_Small_WACV_2024_supplemental.pdf | 2403.06014 | title_snapshot | @InProceedings{Park_2024_WACV,
author = {Park, Jeonghwan and Miller, Paul and McLaughlin, Niall},
title = {Hard-Label Based Small Query Black-Box Adversarial Attack},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | We consider the hard-label based black-box adversarial attack setting which solely observes the target model's predicted class. Most of the attack methods in this setting suffer from impractical number of queries required to achieve a successful attack. One approach to tackle this drawback is utilising the adversarial ... |
Kwon_Learning_to_Detour_Shortcut_Mitigating_Augmentation_for_Weakly_Supervised_Semantic_WACV_2024_paper | Learning to Detour: Shortcut Mitigating Augmentation for Weakly Supervised Semantic Segmentation | [
"JuneHyoung Kwon",
"Eunju Lee",
"Yunsung Cho",
"YoungBin Kim"
] | https://openaccess.thecvf.com/content/WACV2024/html/Kwon_Learning_to_Detour_Shortcut_Mitigating_Augmentation_for_Weakly_Supervised_Semantic_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Kwon_Learning_to_Detour_Shortcut_Mitigating_Augmentation_for_Weakly_Supervised_Semantic_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Kwon_Learning_to_Detour_WACV_2024_supplemental.pdf | 2405.18148 | title_snapshot | @InProceedings{Kwon_2024_WACV,
author = {Kwon, JuneHyoung and Lee, Eunju and Cho, Yunsung and Kim, YoungBin},
title = {Learning to Detour: Shortcut Mitigating Augmentation for Weakly Supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compu... | Weakly supervised semantic segmentation (WSSS) employing weak forms of labels has been actively studied to alleviate the annotation cost of acquiring pixel-level labels. However, classifiers trained on biased datasets tend to exploit shortcut features and make predictions based on spurious correlations between certain ... |
Trinh_3D_Super-Resolution_Model_for_Vehicle_Flow_Field_Enrichment_WACV_2024_paper | 3D Super-Resolution Model for Vehicle Flow Field Enrichment | [
"Thanh Luan Trinh",
"Fangge Chen",
"Takuya Nanri",
"Kei Akasaka"
] | https://openaccess.thecvf.com/content/WACV2024/html/Trinh_3D_Super-Resolution_Model_for_Vehicle_Flow_Field_Enrichment_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Trinh_3D_Super-Resolution_Model_for_Vehicle_Flow_Field_Enrichment_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Trinh_3D_Super-Resolution_Model_WACV_2024_supplemental.pdf | null | null | @InProceedings{Trinh_2024_WACV,
author = {Trinh, Thanh Luan and Chen, Fangge and Nanri, Takuya and Akasaka, Kei},
title = {3D Super-Resolution Model for Vehicle Flow Field Enrichment},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | In vehicle shape design from aerodynamic performance perspective, deep learning methods enable us to estimate the flow field in a short period. However, the estimated flow fields are generally coarse and of low resolution. Therefore, a super-resolution model is required to enrich them. In this study, we propose a novel... |
Liao_Multi-View_3D_Object_Reconstruction_and_Uncertainty_Modelling_With_Neural_Shape_WACV_2024_paper | Multi-View 3D Object Reconstruction and Uncertainty Modelling With Neural Shape Prior | [
"Ziwei Liao",
"Steven L. Waslander"
] | https://openaccess.thecvf.com/content/WACV2024/html/Liao_Multi-View_3D_Object_Reconstruction_and_Uncertainty_Modelling_With_Neural_Shape_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Liao_Multi-View_3D_Object_Reconstruction_and_Uncertainty_Modelling_With_Neural_Shape_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Liao_Multi-View_3D_Object_WACV_2024_supplemental.pdf | 2306.11739 | cvf | @InProceedings{Liao_2024_WACV,
author = {Liao, Ziwei and Waslander, Steven L.},
title = {Multi-View 3D Object Reconstruction and Uncertainty Modelling With Neural Shape Prior},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Janu... | 3D object reconstruction is important for semantic scene understanding. It is challenging to reconstruct detailed 3D shapes from monocular images directly due to a lack of depth information, occlusion and noise. Most current methods generate deterministic object models without any awareness of the uncertainty of the re... |
Djilali_Do_VSR_Models_Generalize_Beyond_LRS3_WACV_2024_paper | Do VSR Models Generalize Beyond LRS3? | [
"Yasser Abdelaziz Dahou Djilali",
"Sanath Narayan",
"Eustache LeBihan",
"Haithem Boussaid",
"Ebtesam Almazrouei",
"Merouane Debbah"
] | https://openaccess.thecvf.com/content/WACV2024/html/Djilali_Do_VSR_Models_Generalize_Beyond_LRS3_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Djilali_Do_VSR_Models_Generalize_Beyond_LRS3_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Djilali_Do_VSR_Models_WACV_2024_supplemental.pdf | 2311.14063 | title_snapshot | @InProceedings{Djilali_2024_WACV,
author = {Djilali, Yasser Abdelaziz Dahou and Narayan, Sanath and LeBihan, Eustache and Boussaid, Haithem and Almazrouei, Ebtesam and Debbah, Merouane},
title = {Do VSR Models Generalize Beyond LRS3?},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on App... | The Lip Reading Sentences-3 (LRS3) benchmark has primarily been the focus of intense research in visual speech recognition (VSR) during the last few years. As a result, there is an increased risk of overfitting to its excessively used test set, which is only one hour duration. To alleviate this issue, we build a new VS... |
Dessalene_Context_in_Human_Action_Through_Motion_Complementarity_WACV_2024_paper | Context in Human Action Through Motion Complementarity | [
"Eadom Dessalene",
"Michael Maynord",
"Cornelia Fermüller",
"Yiannis Aloimonos"
] | https://openaccess.thecvf.com/content/WACV2024/html/Dessalene_Context_in_Human_Action_Through_Motion_Complementarity_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Dessalene_Context_in_Human_Action_Through_Motion_Complementarity_WACV_2024_paper.pdf | null | null | null | @InProceedings{Dessalene_2024_WACV,
author = {Dessalene, Eadom and Maynord, Michael and Ferm\"uller, Cornelia and Aloimonos, Yiannis},
title = {Context in Human Action Through Motion Complementarity},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)... | Motivated by Goldman's Theory of Human Action - a framework in which action decomposes into 1) base physical movements, and 2) the context in which they occur - we propose a novel learning formulation for motion and context, where context is derived as the complement to motion. More specifically, we model physical move... |
Hooda_D4_Detection_of_Adversarial_Diffusion_Deepfakes_Using_Disjoint_Ensembles_WACV_2024_paper | D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles | [
"Ashish Hooda",
"Neal Mangaokar",
"Ryan Feng",
"Kassem Fawaz",
"Somesh Jha",
"Atul Prakash"
] | https://openaccess.thecvf.com/content/WACV2024/html/Hooda_D4_Detection_of_Adversarial_Diffusion_Deepfakes_Using_Disjoint_Ensembles_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Hooda_D4_Detection_of_Adversarial_Diffusion_Deepfakes_Using_Disjoint_Ensembles_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Hooda_D4_Detection_of_WACV_2024_supplemental.pdf | 2202.05687 | cvf | @InProceedings{Hooda_2024_WACV,
author = {Hooda, Ashish and Mangaokar, Neal and Feng, Ryan and Fawaz, Kassem and Jha, Somesh and Prakash, Atul},
title = {D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicati... | Detecting diffusion-generated deepfake images remains an open problem. Current detection methods fail against an adversary who adds imperceptible adversarial perturbations to the deepfake to evade detection. In this work, we propose Disjoint Diffusion Deepfake Detection (D4), a deepfake detector designed to improve bla... |
Di_ProS_Facial_Omni-Representation_Learning_via_Prototype-Based_Self-Distillation_WACV_2024_paper | ProS: Facial Omni-Representation Learning via Prototype-Based Self-Distillation | [
"Xing Di",
"Yiyu Zheng",
"Xiaoming Liu",
"Yu Cheng"
] | https://openaccess.thecvf.com/content/WACV2024/html/Di_ProS_Facial_Omni-Representation_Learning_via_Prototype-Based_Self-Distillation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Di_ProS_Facial_Omni-Representation_Learning_via_Prototype-Based_Self-Distillation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Di_ProS_Facial_Omni-Representation_WACV_2024_supplemental.pdf | 2311.01929 | cvf | @InProceedings{Di_2024_WACV,
author = {Di, Xing and Zheng, Yiyu and Liu, Xiaoming and Cheng, Yu},
title = {ProS: Facial Omni-Representation Learning via Prototype-Based Self-Distillation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | This paper presents a novel approach, called Prototype-based Self-Distillation (ProS), for unsupervised face representation learning. The existing supervised methods heavily rely on a large amount of annotated training facial data, which poses challenges in terms of data collection and privacy concerns. To address thes... |
Li_TCP_Triplet_Contrastive-Relationship_Preserving_for_Class-Incremental_Learning_WACV_2024_paper | TCP: Triplet Contrastive-Relationship Preserving for Class-Incremental Learning | [
"Shiyao Li",
"Xuefei Ning",
"Shanghang Zhang",
"Lidong Guo",
"Tianchen Zhao",
"Huazhong Yang",
"Yu Wang"
] | https://openaccess.thecvf.com/content/WACV2024/html/Li_TCP_Triplet_Contrastive-Relationship_Preserving_for_Class-Incremental_Learning_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Li_TCP_Triplet_Contrastive-Relationship_Preserving_for_Class-Incremental_Learning_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Li_TCP_Triplet_Contrastive-Relationship_WACV_2024_supplemental.pdf | null | null | @InProceedings{Li_2024_WACV,
author = {Li, Shiyao and Ning, Xuefei and Zhang, Shanghang and Guo, Lidong and Zhao, Tianchen and Yang, Huazhong and Wang, Yu},
title = {TCP: Triplet Contrastive-Relationship Preserving for Class-Incremental Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Confe... | In class-incremental learning (CIL), when deep neural networks learn new classes, their recognition performance in old classes will drop significantly. This phenomenon is widely known as catastrophic forgetting. To alleviate catastrophic forgetting, existing methods store a small portion of old class data with a memory... |
Musallam_Self-Supervised_Learning_for_Place_Representation_Generalization_Across_Appearance_Changes_WACV_2024_paper | Self-Supervised Learning for Place Representation Generalization Across Appearance Changes | [
"Mohamed Adel Musallam",
"Vincent Gaudillière",
"Djamila Aouada"
] | https://openaccess.thecvf.com/content/WACV2024/html/Musallam_Self-Supervised_Learning_for_Place_Representation_Generalization_Across_Appearance_Changes_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Musallam_Self-Supervised_Learning_for_Place_Representation_Generalization_Across_Appearance_Changes_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Musallam_Self-Supervised_Learning_for_WACV_2024_supplemental.pdf | 2303.02370 | title_snapshot | @InProceedings{Musallam_2024_WACV,
author = {Musallam, Mohamed Adel and Gaudilli\`ere, Vincent and Aouada, Djamila},
title = {Self-Supervised Learning for Place Representation Generalization Across Appearance Changes},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comp... | Visual place recognition is a key to unlocking spatial navigation for animals, humans and robots. While state-of-the-art approaches are trained in a supervised manner and, therefore, hardly capture the information needed for generalizing to unusual conditions. We argue that self-supervised learning may help abstracting... |
Zhang_Patch-Based_Selection_and_Refinement_for_Early_Object_Detection_WACV_2024_paper | Patch-Based Selection and Refinement for Early Object Detection | [
"Tianyi Zhang",
"Kishore Kasichainula",
"Yaoxin Zhuo",
"Baoxin Li",
"Jae-Sun Seo",
"Yu Cao"
] | https://openaccess.thecvf.com/content/WACV2024/html/Zhang_Patch-Based_Selection_and_Refinement_for_Early_Object_Detection_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Zhang_Patch-Based_Selection_and_Refinement_for_Early_Object_Detection_WACV_2024_paper.pdf | null | 2311.02274 | cvf | @InProceedings{Zhang_2024_WACV,
author = {Zhang, Tianyi and Kasichainula, Kishore and Zhuo, Yaoxin and Li, Baoxin and Seo, Jae-Sun and Cao, Yu},
title = {Patch-Based Selection and Refinement for Early Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Com... | Early object detection (OD) is a crucial task for the safety of many dynamic systems. Current OD algorithms have limited success for small objects at a long distance. To improve the accuracy and efficiency of such a task, we propose a novel set of algorithms that divide the image into patches, select patches with objec... |
Berrada_Guided_Distillation_for_Semi-Supervised_Instance_Segmentation_WACV_2024_paper | Guided Distillation for Semi-Supervised Instance Segmentation | [
"Tariq Berrada",
"Camille Couprie",
"Karteek Alahari",
"Jakob Verbeek"
] | https://openaccess.thecvf.com/content/WACV2024/html/Berrada_Guided_Distillation_for_Semi-Supervised_Instance_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Berrada_Guided_Distillation_for_Semi-Supervised_Instance_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Berrada_Guided_Distillation_for_WACV_2024_supplemental.pdf | 2308.02668 | cvf | @InProceedings{Berrada_2024_WACV,
author = {Berrada, Tariq and Couprie, Camille and Alahari, Karteek and Verbeek, Jakob},
title = {Guided Distillation for Semi-Supervised Instance Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Although instance segmentation methods have improved considerably, the dominant paradigm is to rely on fully annotated training images, which are tedious to obtain. To alleviate this reliance, and boost results, semi-supervised approaches leverage unlabeled data as an additional training signal that limits overfitting ... |
Albanese_Optimizing_Long-Term_Robot_Tracking_With_Multi-Platform_Sensor_Fusion_WACV_2024_paper | Optimizing Long-Term Robot Tracking With Multi-Platform Sensor Fusion | [
"Giuliano Albanese",
"Arka Mitra",
"Jan-Nico Zaech",
"Yupeng Zhao",
"Ajad Chhatkuli",
"Luc Van Gool"
] | https://openaccess.thecvf.com/content/WACV2024/html/Albanese_Optimizing_Long-Term_Robot_Tracking_With_Multi-Platform_Sensor_Fusion_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Albanese_Optimizing_Long-Term_Robot_Tracking_With_Multi-Platform_Sensor_Fusion_WACV_2024_paper.pdf | null | null | null | @InProceedings{Albanese_2024_WACV,
author = {Albanese, Giuliano and Mitra, Arka and Zaech, Jan-Nico and Zhao, Yupeng and Chhatkuli, Ajad and Van Gool, Luc},
title = {Optimizing Long-Term Robot Tracking With Multi-Platform Sensor Fusion},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on A... | Monitoring a fleet of robots requires stable long-term tracking with re-identification, which is yet an unsolved challenge in many scenarios. One application of this is the analysis of autonomous robotic soccer games at RoboCup. Tracking in these games requires handling of identically looking players, strong occlusions... |
Mehta_HyperMix_Out-of-Distribution_Detection_and_Classification_in_Few-Shot_Settings_WACV_2024_paper | HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings | [
"Nikhil Mehta",
"Kevin J. Liang",
"Jing Huang",
"Fu-Jen Chu",
"Li Yin",
"Tal Hassner"
] | https://openaccess.thecvf.com/content/WACV2024/html/Mehta_HyperMix_Out-of-Distribution_Detection_and_Classification_in_Few-Shot_Settings_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Mehta_HyperMix_Out-of-Distribution_Detection_and_Classification_in_Few-Shot_Settings_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Mehta_HyperMix_Out-of-Distribution_Detection_WACV_2024_supplemental.pdf | 2312.15086 | title_snapshot | @InProceedings{Mehta_2024_WACV,
author = {Mehta, Nikhil and Liang, Kevin J. and Huang, Jing and Chu, Fu-Jen and Yin, Li and Hassner, Tal},
title = {HyperMix: Out-of-Distribution Detection and Classification in Few-Shot Settings},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicati... | Out-of-distribution (OOD) detection is an important topic for real-world machine learning systems, but settings with limited in-distribution samples have been underexplored. Such few-shot OOD settings are challenging, as models have scarce opportunities to learn the data distribution before being tasked with identifyin... |
Bhattarai_TriPlaneNet_An_Encoder_for_EG3D_Inversion_WACV_2024_paper | TriPlaneNet: An Encoder for EG3D Inversion | [
"Ananta R. Bhattarai",
"Matthias Nießner",
"Artem Sevastopolsky"
] | https://openaccess.thecvf.com/content/WACV2024/html/Bhattarai_TriPlaneNet_An_Encoder_for_EG3D_Inversion_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Bhattarai_TriPlaneNet_An_Encoder_for_EG3D_Inversion_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Bhattarai_TriPlaneNet_An_Encoder_WACV_2024_supplemental.pdf | 2303.13497 | title_snapshot | @InProceedings{Bhattarai_2024_WACV,
author = {Bhattarai, Ananta R. and Nie{\ss}ner, Matthias and Sevastopolsky, Artem},
title = {TriPlaneNet: An Encoder for EG3D Inversion},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January... | Recent progress in NeRF-based GANs has introduced a number of approaches for high-resolution and high-fidelity generative modeling of human heads with a possibility for novel view rendering. At the same time, one must solve an inverse problem to be able to re-render or modify an existing image or video. Despite the suc... |
Anderson_Elusive_Images_Beyond_Coarse_Analysis_for_Fine-Grained_Recognition_WACV_2024_paper | Elusive Images: Beyond Coarse Analysis for Fine-Grained Recognition | [
"Connor Anderson",
"Matt Gwilliam",
"Evelyn Gaskin",
"Ryan Farrell"
] | https://openaccess.thecvf.com/content/WACV2024/html/Anderson_Elusive_Images_Beyond_Coarse_Analysis_for_Fine-Grained_Recognition_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Anderson_Elusive_Images_Beyond_Coarse_Analysis_for_Fine-Grained_Recognition_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Anderson_Elusive_Images_Beyond_WACV_2024_supplemental.pdf | null | null | @InProceedings{Anderson_2024_WACV,
author = {Anderson, Connor and Gwilliam, Matt and Gaskin, Evelyn and Farrell, Ryan},
title = {Elusive Images: Beyond Coarse Analysis for Fine-Grained Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},... | While the community has seen many advances in recent years to address the challenging problem of Finegrained Visual Categorization (FGVC), progress seems to be slowing--new state-of-the-art methods often distinguish themselves by improving top-1 accuracy by mere tenths of a percent. However, across all of the now-stand... |
Dunnhofer_Tracking_Skiers_From_the_Top_to_the_Bottom_WACV_2024_paper | Tracking Skiers From the Top to the Bottom | [
"Matteo Dunnhofer",
"Luca Sordi",
"Niki Martinel",
"Christian Micheloni"
] | https://openaccess.thecvf.com/content/WACV2024/html/Dunnhofer_Tracking_Skiers_From_the_Top_to_the_Bottom_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Dunnhofer_Tracking_Skiers_From_the_Top_to_the_Bottom_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Dunnhofer_Tracking_Skiers_From_WACV_2024_supplemental.pdf | 2312.09723 | cvf | @InProceedings{Dunnhofer_2024_WACV,
author = {Dunnhofer, Matteo and Sordi, Luca and Martinel, Niki and Micheloni, Christian},
title = {Tracking Skiers From the Top to the Bottom},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {J... | Skiing is a popular winter sport discipline with a long history of competitive events. In this domain, computer vision has the potential to enhance the understanding of athletes' performance, but its application lags behind other sports due to limited studies and datasets. This paper makes a step forward in filling suc... |
Liu_BPKD_Boundary_Privileged_Knowledge_Distillation_for_Semantic_Segmentation_WACV_2024_paper | BPKD: Boundary Privileged Knowledge Distillation for Semantic Segmentation | [
"Liyang Liu",
"Zihan Wang",
"Minh Hieu Phan",
"Bowen Zhang",
"Jinchao Ge",
"Yifan Liu"
] | https://openaccess.thecvf.com/content/WACV2024/html/Liu_BPKD_Boundary_Privileged_Knowledge_Distillation_for_Semantic_Segmentation_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Liu_BPKD_Boundary_Privileged_Knowledge_Distillation_for_Semantic_Segmentation_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Liu_BPKD_Boundary_Privileged_WACV_2024_supplemental.pdf | 2306.08075 | cvf | @InProceedings{Liu_2024_WACV,
author = {Liu, Liyang and Wang, Zihan and Phan, Minh Hieu and Zhang, Bowen and Ge, Jinchao and Liu, Yifan},
title = {BPKD: Boundary Privileged Knowledge Distillation for Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of... | Current knowledge distillation approaches in semantic segmentation tend to adopt a holistic approach that treats all spatial locations equally. However, for dense prediction, students' predictions on edge regions are highly uncertain due to contextual information leakage, requiring higher spatial sensitivity knowledge ... |
Xia_DREAM_Visual_Decoding_From_Reversing_Human_Visual_System_WACV_2024_paper | DREAM: Visual Decoding From Reversing Human Visual System | [
"Weihao Xia",
"Raoul de Charette",
"Cengiz Oztireli",
"Jing-Hao Xue"
] | https://openaccess.thecvf.com/content/WACV2024/html/Xia_DREAM_Visual_Decoding_From_Reversing_Human_Visual_System_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Xia_DREAM_Visual_Decoding_From_Reversing_Human_Visual_System_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Xia_DREAM_Visual_Decoding_WACV_2024_supplemental.pdf | 2310.02265 | cvf | @InProceedings{Xia_2024_WACV,
author = {Xia, Weihao and de Charette, Raoul and Oztireli, Cengiz and Xue, Jing-Hao},
title = {DREAM: Visual Decoding From Reversing Human Visual System},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | In this work we present DREAM, an fMRI-to-image method for reconstructing viewed images from brain activities, grounded on fundamental knowledge of the human visual system. We craft reverse pathways that emulate the hierarchical and parallel nature of how humans perceive the visual world. These tailored pathways are sp... |
Felt_Seeing_Stars_Learned_Star_Localization_for_Narrow-Field_Astrometry_WACV_2024_paper | Seeing Stars: Learned Star Localization for Narrow-Field Astrometry | [
"Violet Felt",
"Justin Fletcher"
] | https://openaccess.thecvf.com/content/WACV2024/html/Felt_Seeing_Stars_Learned_Star_Localization_for_Narrow-Field_Astrometry_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Felt_Seeing_Stars_Learned_Star_Localization_for_Narrow-Field_Astrometry_WACV_2024_paper.pdf | null | null | null | @InProceedings{Felt_2024_WACV,
author = {Felt, Violet and Fletcher, Justin},
title = {Seeing Stars: Learned Star Localization for Narrow-Field Astrometry},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year =... | Star localization in astronomical imagery is a computer vision task that underpins satellite tracking. Astronomical star extraction techniques often struggle to detect stars when applied to satellite tracking imagery due to the narrower fields of view and rate track observational modes of satellite tracking telescopes.... |
Demir_How_Do_Deepfakes_Move_Motion_Magnification_for_Deepfake_Source_Detection_WACV_2024_paper | How Do Deepfakes Move? Motion Magnification for Deepfake Source Detection | [
"Ilke Demir",
"Umur Aybars Çiftçi"
] | https://openaccess.thecvf.com/content/WACV2024/html/Demir_How_Do_Deepfakes_Move_Motion_Magnification_for_Deepfake_Source_Detection_WACV_2024_paper.html | https://openaccess.thecvf.com/content/WACV2024/papers/Demir_How_Do_Deepfakes_Move_Motion_Magnification_for_Deepfake_Source_Detection_WACV_2024_paper.pdf | https://openaccess.thecvf.com/content/WACV2024/supplemental/Demir_How_Do_Deepfakes_WACV_2024_supplemental.pdf | 2212.14033 | title_snapshot | @InProceedings{Demir_2024_WACV,
author = {Demir, Ilke and \c{C}ift\c{c}i, Umur Aybars},
title = {How Do Deepfakes Move? Motion Magnification for Deepfake Source Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January}... | With the proliferation of deep generative models, deepfakes are improving in quality and quantity everyday. However, there are subtle authenticity signals in pristine videos, not replicated by current generative models. We contrast the movement in deepfakes and authentic videos by motion magnification towards building ... |
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