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 44 122 | title stringlengths 22 143 | authors listlengths 1 13 | cvf_url stringlengths 101 179 | pdf_url stringlengths 102 180 | supp_url stringlengths 102 143 ⌀ | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 3
values | bibtex large_stringlengths 315 613 | abstract large_stringlengths 593 1.96k |
|---|---|---|---|---|---|---|---|---|---|
Fortin_Towards_Contextual_Learning_in_Few-Shot_Object_Classification_WACV_2021_paper | Towards Contextual Learning in Few-Shot Object Classification | [
"Mathieu Page Fortin",
"Brahim Chaib-draa"
] | https://openaccess.thecvf.com/content/WACV2021/html/Fortin_Towards_Contextual_Learning_in_Few-Shot_Object_Classification_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Fortin_Towards_Contextual_Learning_in_Few-Shot_Object_Classification_WACV_2021_paper.pdf | null | 1912.06679 | title_snapshot | @InProceedings{Fortin_2021_WACV,
author = {Fortin, Mathieu Page and Chaib-draa, Brahim},
title = {Towards Contextual Learning in Few-Shot Object Classification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Few-shot Learning (FSL) aims to classify new concepts from a small number of examples. While there have been an increasing amount of work on few-shot object classification in the last few years, most current approaches are limited to images with only one centered object. On the opposite, humans are able to leverage pri... |
Patro_Multimodal_Humor_Dataset_Predicting_Laughter_Tracks_for_Sitcoms_WACV_2021_paper | Multimodal Humor Dataset: Predicting Laughter Tracks for Sitcoms | [
"Badri N. Patro",
"Mayank Lunayach",
"Deepankar Srivastava",
"Sarvesh",
"Hunar Singh",
"Vinay P. Namboodiri"
] | https://openaccess.thecvf.com/content/WACV2021/html/Patro_Multimodal_Humor_Dataset_Predicting_Laughter_Tracks_for_Sitcoms_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Patro_Multimodal_Humor_Dataset_Predicting_Laughter_Tracks_for_Sitcoms_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Patro_Multimodal_Humor_Dataset_WACV_2021_supplemental.pdf | null | null | @InProceedings{Patro_2021_WACV,
author = {Patro, Badri N. and Lunayach, Mayank and Srivastava, Deepankar and Sarvesh and Singh, Hunar and Namboodiri, Vinay P.},
title = {Multimodal Humor Dataset: Predicting Laughter Tracks for Sitcoms},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Ap... | A great number of situational comedies (sitcoms) are being regularly made and the task of adding laughter tracks to these is a critical task. Providing an ability to be able to predict whether something will be humorous to the audience is also crucial. In this project, we aim to automate this task. Towards doing so, we... |
Achituve_Self-Supervised_Learning_for_Domain_Adaptation_on_Point_Clouds_WACV_2021_paper | Self-Supervised Learning for Domain Adaptation on Point Clouds | [
"Idan Achituve",
"Haggai Maron",
"Gal Chechik"
] | https://openaccess.thecvf.com/content/WACV2021/html/Achituve_Self-Supervised_Learning_for_Domain_Adaptation_on_Point_Clouds_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Achituve_Self-Supervised_Learning_for_Domain_Adaptation_on_Point_Clouds_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Achituve_Self-Supervised_Learning_for_WACV_2021_supplemental.pdf | 2003.12641 | cvf | @InProceedings{Achituve_2021_WACV,
author = {Achituve, Idan and Maron, Haggai and Chechik, Gal},
title = {Self-Supervised Learning for Domain Adaptation on Point Clouds},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | Self-supervised learning (SSL) is a technique for learning useful representations from unlabeled data. It has been applied effectively to domain adaptation (DA) on images and videos. It is still unknown if and how it can be leveraged for domain adaptation in 3D perception problems. Here we describe the first study of S... |
Peng_Efficient_3D_Video_Engine_Using_Frame_Redundancy_WACV_2021_paper | Efficient 3D Video Engine Using Frame Redundancy | [
"Gao Peng",
"Bo Pang",
"Cewu Lu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Peng_Efficient_3D_Video_Engine_Using_Frame_Redundancy_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Peng_Efficient_3D_Video_Engine_Using_Frame_Redundancy_WACV_2021_paper.pdf | null | null | null | @InProceedings{Peng_2021_WACV,
author = {Peng, Gao and Pang, Bo and Lu, Cewu},
title = {Efficient 3D Video Engine Using Frame Redundancy},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
page... | Traditional 3d video understanding methods process videos frame by frame. We argue that a lot of computation in this mechanism is redundant based on a key observation - adjacent frames in 3D videos have visually similar geometry structure. To handle the redundancy, we propose the Efficient 3D Video Engine (EVE), aiming... |
Kahatapitiya_Exploiting_the_Redundancy_in_Convolutional_Filters_for_Parameter_Reduction_WACV_2021_paper | Exploiting the Redundancy in Convolutional Filters for Parameter Reduction | [
"Kumara Kahatapitiya",
"Ranga Rodrigo"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kahatapitiya_Exploiting_the_Redundancy_in_Convolutional_Filters_for_Parameter_Reduction_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kahatapitiya_Exploiting_the_Redundancy_in_Convolutional_Filters_for_Parameter_Reduction_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kahatapitiya_Exploiting_the_Redundancy_WACV_2021_supplemental.pdf | 1907.11432 | cvf | @InProceedings{Kahatapitiya_2021_WACV,
author = {Kahatapitiya, Kumara and Rodrigo, Ranga},
title = {Exploiting the Redundancy in Convolutional Filters for Parameter Reduction},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Janu... | Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in many computer vision tasks over the years. However, this comes at the cost of heavy computation and memory intensive network designs, suggesting potential improvements in efficiency. Convolutional layers of CNNs partly account for such a... |
Kotseruba_Benchmark_for_Evaluating_Pedestrian_Action_Prediction_WACV_2021_paper | Benchmark for Evaluating Pedestrian Action Prediction | [
"Iuliia Kotseruba",
"Amir Rasouli",
"John K. Tsotsos"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kotseruba_Benchmark_for_Evaluating_Pedestrian_Action_Prediction_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kotseruba_Benchmark_for_Evaluating_Pedestrian_Action_Prediction_WACV_2021_paper.pdf | null | null | null | @InProceedings{Kotseruba_2021_WACV,
author = {Kotseruba, Iuliia and Rasouli, Amir and Tsotsos, John K.},
title = {Benchmark for Evaluating Pedestrian Action Prediction},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | Pedestrian action prediction has been a topic of active research in recent years resulting in many new algorithmic solutions. However, measuring the overall progress towards solving this problem is difficult due to the lack of publicly available benchmarks and common training and evaluation procedures. To this end, we ... |
Khan_Regional_Attention_Networks_With_Context-Aware_Fusion_for_Group_Emotion_Recognition_WACV_2021_paper | Regional Attention Networks With Context-Aware Fusion for Group Emotion Recognition | [
"Ahmed Shehab Khan",
"Zhiyuan Li",
"Jie Cai",
"Yan Tong"
] | https://openaccess.thecvf.com/content/WACV2021/html/Khan_Regional_Attention_Networks_With_Context-Aware_Fusion_for_Group_Emotion_Recognition_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Khan_Regional_Attention_Networks_With_Context-Aware_Fusion_for_Group_Emotion_Recognition_WACV_2021_paper.pdf | null | null | null | @InProceedings{Khan_2021_WACV,
author = {Khan, Ahmed Shehab and Li, Zhiyuan and Cai, Jie and Tong, Yan},
title = {Regional Attention Networks With Context-Aware Fusion for Group Emotion Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}... | Group Emotion Recognition (GER) from images has many inherent challenges. Specifically, it is difficult to combine diverse emotions of different individuals into a single conclusive label. In addition, although utilization of information other than faces like scene and objects has proven helpful, it is still a challeng... |
Desai_Auxiliary_Tasks_for_Efficient_Learning_of_Point-Goal_Navigation_WACV_2021_paper | Auxiliary Tasks for Efficient Learning of Point-Goal Navigation | [
"Saurabh Satish Desai",
"Stefan Lee"
] | https://openaccess.thecvf.com/content/WACV2021/html/Desai_Auxiliary_Tasks_for_Efficient_Learning_of_Point-Goal_Navigation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Desai_Auxiliary_Tasks_for_Efficient_Learning_of_Point-Goal_Navigation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Desai_Auxiliary_Tasks_for_WACV_2021_supplemental.pdf | null | null | @InProceedings{Desai_2021_WACV,
author = {Desai, Saurabh Satish and Lee, Stefan},
title = {Auxiliary Tasks for Efficient Learning of Point-Goal Navigation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Top-performing approaches to embodied AI tasks like point-goal navigation often rely on training agents via reinforcement learning over tens of millions (or even billions) of experiential steps -- learning neural agents that map directly from visual observations to actions. In this work, we question whether these extre... |
Zhu_Cross-Modality_3D_Object_Detection_WACV_2021_paper | Cross-Modality 3D Object Detection | [
"Ming Zhu",
"Chao Ma",
"Pan Ji",
"Xiaokang Yang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhu_Cross-Modality_3D_Object_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhu_Cross-Modality_3D_Object_Detection_WACV_2021_paper.pdf | null | 2008.10436 | cvf | @InProceedings{Zhu_2021_WACV,
author = {Zhu, Ming and Ma, Chao and Ji, Pan and Yang, Xiaokang},
title = {Cross-Modality 3D Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
p... | In this paper, we focus on exploring the fusion of images and point clouds for 3D object detection in view of the complementary nature of the two modalities, i.e., images possess more semantic information while point clouds specialize in distance sensing. To this end, we present a novel two-stage multi-modal fusion net... |
Wang_Variational_Prototype_Inference_for_Few-Shot_Semantic_Segmentation_WACV_2021_paper | Variational Prototype Inference for Few-Shot Semantic Segmentation | [
"Haochen Wang",
"Yandan Yang",
"Xianbin Cao",
"Xiantong Zhen",
"Cees Snoek",
"Ling Shao"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wang_Variational_Prototype_Inference_for_Few-Shot_Semantic_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wang_Variational_Prototype_Inference_for_Few-Shot_Semantic_Segmentation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Wang_Variational_Prototype_Inference_WACV_2021_supplemental.pdf | null | null | @InProceedings{Wang_2021_WACV,
author = {Wang, Haochen and Yang, Yandan and Cao, Xianbin and Zhen, Xiantong and Snoek, Cees and Shao, Ling},
title = {Variational Prototype Inference for Few-Shot Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comp... | In this paper, we propose variational prototype inference to address few-shot semantic segmentation in a probabilistic framework. A probabilistic latent variable model infers the distribution of the prototype that is treated as the latent variable. We formulate the optimization as a variational inference problem, which... |
Wang_Zero-Shot_Recognition_via_Optimal_Transport_WACV_2021_paper | Zero-Shot Recognition via Optimal Transport | [
"Wenlin Wang",
"Hongteng Xu",
"Guoyin Wang",
"Wenqi Wang",
"Lawrence Carin"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wang_Zero-Shot_Recognition_via_Optimal_Transport_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wang_Zero-Shot_Recognition_via_Optimal_Transport_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Wang_Zero-Shot_Recognition_via_WACV_2021_supplemental.pdf | 1910.09057 | title_snapshot | @InProceedings{Wang_2021_WACV,
author = {Wang, Wenlin and Xu, Hongteng and Wang, Guoyin and Wang, Wenqi and Carin, Lawrence},
title = {Zero-Shot Recognition via Optimal Transport},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {... | We propose an optimal transport (OT) framework for generalized zero-shot learning (GZSL), seeking to distinguish samples for both seen and unseen classes, with the assist of auxiliary attributes. The discrepancy between features and attributes is minimized by solving an optimal transport problem. Specifically, we buil... |
Mafla_Multi-Modal_Reasoning_Graph_for_Scene-Text_Based_Fine-Grained_Image_Classification_and_WACV_2021_paper | Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval | [
"Andres Mafla",
"Sounak Dey",
"Ali Furkan Biten",
"Lluis Gomez",
"Dimosthenis Karatzas"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mafla_Multi-Modal_Reasoning_Graph_for_Scene-Text_Based_Fine-Grained_Image_Classification_and_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mafla_Multi-Modal_Reasoning_Graph_for_Scene-Text_Based_Fine-Grained_Image_Classification_and_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Mafla_Multi-Modal_Reasoning_Graph_WACV_2021_supplemental.pdf | 2009.09809 | cvf | @InProceedings{Mafla_2021_WACV,
author = {Mafla, Andres and Dey, Sounak and Biten, Ali Furkan and Gomez, Lluis and Karatzas, Dimosthenis},
title = {Multi-Modal Reasoning Graph for Scene-Text Based Fine-Grained Image Classification and Retrieval},
booktitle = {Proceedings of the IEEE/CVF Winter Confer... | Scene text instances found in natural images carry explicit semantic information that can provide important cues to solve a wide array of computer vision problems. In this paper, we focus on leveraging multi-modal content in the form of visual and textual cues to tackle the task of fine-grained image classification and... |
Guo_PI-Net_Pose_Interacting_Network_for_Multi-Person_Monocular_3D_Pose_Estimation_WACV_2021_paper | PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation | [
"Wen Guo",
"Enric Corona",
"Francesc Moreno-Noguer",
"Xavier Alameda-Pineda"
] | https://openaccess.thecvf.com/content/WACV2021/html/Guo_PI-Net_Pose_Interacting_Network_for_Multi-Person_Monocular_3D_Pose_Estimation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Guo_PI-Net_Pose_Interacting_Network_for_Multi-Person_Monocular_3D_Pose_Estimation_WACV_2021_paper.pdf | null | 2010.05302 | title_snapshot | @InProceedings{Guo_2021_WACV,
author = {Guo, Wen and Corona, Enric and Moreno-Noguer, Francesc and Alameda-Pineda, Xavier},
title = {PI-Net: Pose Interacting Network for Multi-Person Monocular 3D Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer ... | Recent literature addressed the monocular 3D pose estimation task very satisfactorily. In these studies, different persons are usually treated as independent pose instances to estimate. However, in many every-day situations, people are interacting, and the pose of an individual depends on the pose of his/her interactee... |
Marques_Size-Invariant_Detection_of_Marine_Vessels_From_Visual_Time_Series_WACV_2021_paper | Size-Invariant Detection of Marine Vessels From Visual Time Series | [
"Tunai Porto Marques",
"Alexandra Branzan Albu",
"Patrick O'Hara",
"Norma Serra",
"Ben Morrow",
"Lauren McWhinnie",
"Rosaline Canessa"
] | https://openaccess.thecvf.com/content/WACV2021/html/Marques_Size-Invariant_Detection_of_Marine_Vessels_From_Visual_Time_Series_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Marques_Size-Invariant_Detection_of_Marine_Vessels_From_Visual_Time_Series_WACV_2021_paper.pdf | null | null | null | @InProceedings{Marques_2021_WACV,
author = {Marques, Tunai Porto and Albu, Alexandra Branzan and O'Hara, Patrick and Serra, Norma and Morrow, Ben and McWhinnie, Lauren and Canessa, Rosaline},
title = {Size-Invariant Detection of Marine Vessels From Visual Time Series},
booktitle = {Proceedings of the... | Marine vessel traffic is one of the main sources of negative anthropogenic impact upon marine environments. The automatic identification of boats in monitoring images facilitates conservation, research and patrolling efforts. However, the diverse sizes of vessels, the highly dynamic water surface and weather-related vi... |
Ayral_Temporal_Stochastic_Softmax_for_3D_CNNs_An_Application_in_Facial_WACV_2021_paper | Temporal Stochastic Softmax for 3D CNNs: An Application in Facial Expression Recognition | [
"Theo Ayral",
"Marco Pedersoli",
"Simon Bacon",
"Eric Granger"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ayral_Temporal_Stochastic_Softmax_for_3D_CNNs_An_Application_in_Facial_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ayral_Temporal_Stochastic_Softmax_for_3D_CNNs_An_Application_in_Facial_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Ayral_Temporal_Stochastic_Softmax_WACV_2021_supplemental.pdf | 2011.05227 | cvf | @InProceedings{Ayral_2021_WACV,
author = {Ayral, Theo and Pedersoli, Marco and Bacon, Simon and Granger, Eric},
title = {Temporal Stochastic Softmax for 3D CNNs: An Application in Facial Expression Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vi... | Training deep learning models for accurate spatiotemporal recognition of facial expressions in videos requires significant computational resources. For practical reasons, 3D Convolutional Neural Networks (3D CNNs) are usually trained with relatively short clips randomly extracted from videos. However, such uniform samp... |
Deng_Scale_Aware_Adaptation_for_Land-Cover_Classification_in_Remote_Sensing_Imagery_WACV_2021_paper | Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery | [
"Xueqing Deng",
"Yi Zhu",
"Yuxin Tian",
"Shawn Newsam"
] | https://openaccess.thecvf.com/content/WACV2021/html/Deng_Scale_Aware_Adaptation_for_Land-Cover_Classification_in_Remote_Sensing_Imagery_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Deng_Scale_Aware_Adaptation_for_Land-Cover_Classification_in_Remote_Sensing_Imagery_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Deng_Scale_Aware_Adaptation_WACV_2021_supplemental.pdf | 2012.04222 | cvf | @InProceedings{Deng_2021_WACV,
author = {Deng, Xueqing and Zhu, Yi and Tian, Yuxin and Newsam, Shawn},
title = {Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
m... | Land-cover classification using remote sensing imagery is an important Earth observation task. Recently, land cover classification has benefited from the development of fully connected neural networks for semantic segmentation. The benchmark datasets available for training deep segmentation models in remote sensing ima... |
Hao_Intro_and_Recap_Detection_for_Movies_and_TV_Series_WACV_2021_paper | Intro and Recap Detection for Movies and TV Series | [
"Xiang Hao",
"Kripa Chettiar",
"Ben Cheung",
"Vernon Germano",
"Raffay Hamid"
] | https://openaccess.thecvf.com/content/WACV2021/html/Hao_Intro_and_Recap_Detection_for_Movies_and_TV_Series_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Hao_Intro_and_Recap_Detection_for_Movies_and_TV_Series_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Hao_Intro_and_Recap_WACV_2021_supplemental.pdf | null | null | @InProceedings{Hao_2021_WACV,
author = {Hao, Xiang and Chettiar, Kripa and Cheung, Ben and Germano, Vernon and Hamid, Raffay},
title = {Intro and Recap Detection for Movies and TV Series},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | Modern video streaming service companies offer millions of video-titles for its customers. A lot of these titles have repetitive introductory and recap parts in the beginning that customers have to manually skip in order to achieve an uninterrupted viewing experience. To avoid this unnecessary friction, some of the ser... |
Wang_Supervoxel_Attention_Graphs_for_Long-Range_Video_Modeling_WACV_2021_paper | Supervoxel Attention Graphs for Long-Range Video Modeling | [
"Yang Wang",
"Gedas Bertasius",
"Tae-Hyun Oh",
"Abhinav Gupta",
"Minh Hoai",
"Lorenzo Torresani"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wang_Supervoxel_Attention_Graphs_for_Long-Range_Video_Modeling_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wang_Supervoxel_Attention_Graphs_for_Long-Range_Video_Modeling_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Wang_Supervoxel_Attention_Graphs_WACV_2021_supplemental.pdf | null | null | @InProceedings{Wang_2021_WACV,
author = {Wang, Yang and Bertasius, Gedas and Oh, Tae-Hyun and Gupta, Abhinav and Hoai, Minh and Torresani, Lorenzo},
title = {Supervoxel Attention Graphs for Long-Range Video Modeling},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compu... | A significant challenge in video understanding is posed by the high dimensionality of the input, which induces large computational cost and high memory footprints. Deep convolutional models operating on video apply pooling and striding to reduce feature dimensionality and to increase the receptive field. However, despi... |
Yeh_SoFA_Source-Data-Free_Feature_Alignment_for_Unsupervised_Domain_Adaptation_WACV_2021_paper | SoFA: Source-Data-Free Feature Alignment for Unsupervised Domain Adaptation | [
"Hao-Wei Yeh",
"Baoyao Yang",
"Pong C. Yuen",
"Tatsuya Harada"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yeh_SoFA_Source-Data-Free_Feature_Alignment_for_Unsupervised_Domain_Adaptation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yeh_SoFA_Source-Data-Free_Feature_Alignment_for_Unsupervised_Domain_Adaptation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Yeh_SoFA_Source-Data-Free_Feature_WACV_2021_supplemental.pdf | null | null | @InProceedings{Yeh_2021_WACV,
author = {Yeh, Hao-Wei and Yang, Baoyao and Yuen, Pong C. and Harada, Tatsuya},
title = {SoFA: Source-Data-Free Feature Alignment for Unsupervised Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Applying a trained model on a new scenario may suffer from domain shift. Unsupervised domain adaptation (UDA) has been proven to be an effective approach to solve the problem of domain shift by leveraging both data from the scenario that the model was trained on (source) and the new scenario (target). Although the sour... |
Li_Towards_Visually_Explaining_Video_Understanding_Networks_With_Perturbation_WACV_2021_paper | Towards Visually Explaining Video Understanding Networks With Perturbation | [
"Zhenqiang Li",
"Weimin Wang",
"Zuoyue Li",
"Yifei Huang",
"Yoichi Sato"
] | https://openaccess.thecvf.com/content/WACV2021/html/Li_Towards_Visually_Explaining_Video_Understanding_Networks_With_Perturbation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Li_Towards_Visually_Explaining_Video_Understanding_Networks_With_Perturbation_WACV_2021_paper.pdf | null | 2005.00375 | cvf | @InProceedings{Li_2021_WACV,
author = {Li, Zhenqiang and Wang, Weimin and Li, Zuoyue and Huang, Yifei and Sato, Yoichi},
title = {Towards Visually Explaining Video Understanding Networks With Perturbation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision ... | 'Making black box models explainable' is a vital problem that accompanies the development of deep learning networks. For networks taking visual information as input, one basic but challenging explanation method is to identify and visualize the input pixels/regions that dominate the network's prediction. However, most e... |
Zhao_Continual_Representation_Learning_for_Biometric_Identification_WACV_2021_paper | Continual Representation Learning for Biometric Identification | [
"Bo Zhao",
"Shixiang Tang",
"Dapeng Chen",
"Hakan Bilen",
"Rui Zhao"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhao_Continual_Representation_Learning_for_Biometric_Identification_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhao_Continual_Representation_Learning_for_Biometric_Identification_WACV_2021_paper.pdf | null | 2006.04455 | cvf | @InProceedings{Zhao_2021_WACV,
author = {Zhao, Bo and Tang, Shixiang and Chen, Dapeng and Bilen, Hakan and Zhao, Rui},
title = {Continual Representation Learning for Biometric Identification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
m... | With the explosion of digital data in recent years, continuously learning new tasks from a stream of data without forgetting previously acquired knowledge has become increasingly important. In this paper, we propose a new continual learning (CL) setting, namely "continual representation learning", which focuses on lear... |
Xie_MUSCLE_Strengthening_Semi-Supervised_Learning_via_Concurrent_Unsupervised_Learning_Using_Mutual_WACV_2021_paper | MUSCLE: Strengthening Semi-Supervised Learning via Concurrent Unsupervised Learning Using Mutual Information Maximization | [
"Hanchen Xie",
"Mohamed E. Hussein",
"Aram Galstyan",
"Wael Abd-Almageed"
] | https://openaccess.thecvf.com/content/WACV2021/html/Xie_MUSCLE_Strengthening_Semi-Supervised_Learning_via_Concurrent_Unsupervised_Learning_Using_Mutual_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Xie_MUSCLE_Strengthening_Semi-Supervised_Learning_via_Concurrent_Unsupervised_Learning_Using_Mutual_WACV_2021_paper.pdf | null | 2012.00150 | cvf | @InProceedings{Xie_2021_WACV,
author = {Xie, Hanchen and Hussein, Mohamed E. and Galstyan, Aram and Abd-Almageed, Wael},
title = {MUSCLE: Strengthening Semi-Supervised Learning via Concurrent Unsupervised Learning Using Mutual Information Maximization},
booktitle = {Proceedings of the IEEE/CVF Winter... | Deep neural networks are powerful, massively parameterized machine learning models that have been shown to perform well in supervised learning tasks. However, very large amounts of labeled data are usually needed to train deep neural networks. Several semi-supervised learning approaches have been proposed to train neur... |
Mazumder_AVGZSLNet_Audio-Visual_Generalized_Zero-Shot_Learning_by_Reconstructing_Label_Features_From_WACV_2021_paper | AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features From Multi-Modal Embeddings | [
"Pratik Mazumder",
"Pravendra Singh",
"Kranti Kumar Parida",
"Vinay P. Namboodiri"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mazumder_AVGZSLNet_Audio-Visual_Generalized_Zero-Shot_Learning_by_Reconstructing_Label_Features_From_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mazumder_AVGZSLNet_Audio-Visual_Generalized_Zero-Shot_Learning_by_Reconstructing_Label_Features_From_WACV_2021_paper.pdf | null | 2005.13402 | cvf | @InProceedings{Mazumder_2021_WACV,
author = {Mazumder, Pratik and Singh, Pravendra and Parida, Kranti Kumar and Namboodiri, Vinay P.},
title = {AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features From Multi-Modal Embeddings},
booktitle = {Proceedings of the IEEE/CV... | In this paper, we propose a novel approach for generalized zero-shot learning in a multi-modal setting, where we have novel classes of audio/video during testing that are not seen during training. We use the semantic relatedness of text embeddings as a means for zero-shot learning by aligning audio and video embeddings... |
Yang_Continuous_Geodesic_Convolutions_for_Learning_on_3D_Shapes_WACV_2021_paper | Continuous Geodesic Convolutions for Learning on 3D Shapes | [
"Zhangsihao Yang",
"Or Litany",
"Tolga Birdal",
"Srinath Sridhar",
"Leonidas Guibas"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yang_Continuous_Geodesic_Convolutions_for_Learning_on_3D_Shapes_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yang_Continuous_Geodesic_Convolutions_for_Learning_on_3D_Shapes_WACV_2021_paper.pdf | null | 2002.02506 | cvf | @InProceedings{Yang_2021_WACV,
author = {Yang, Zhangsihao and Litany, Or and Birdal, Tolga and Sridhar, Srinath and Guibas, Leonidas},
title = {Continuous Geodesic Convolutions for Learning on 3D Shapes},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | The majority of descriptor-based methods for geometric processing of non-rigid shape rely on hand-crafted descriptors. Recently, learning-based techniques have been shown effective, achieving state-of-the-art results in a variety of tasks. Yet, even though these methods can in principle work directly on raw data, most ... |
Kassubeck_Shape_From_Caustics_Reconstruction_of_3D-Printed_Glass_From_Simulated_Caustic_WACV_2021_paper | Shape From Caustics: Reconstruction of 3D-Printed Glass From Simulated Caustic Images | [
"Marc Kassubeck",
"Florian Burgel",
"Susana Castillo",
"Sebastian Stiller",
"Marcus Magnor"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kassubeck_Shape_From_Caustics_Reconstruction_of_3D-Printed_Glass_From_Simulated_Caustic_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kassubeck_Shape_From_Caustics_Reconstruction_of_3D-Printed_Glass_From_Simulated_Caustic_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kassubeck_Shape_From_Caustics_WACV_2021_supplemental.pdf | null | null | @InProceedings{Kassubeck_2021_WACV,
author = {Kassubeck, Marc and Burgel, Florian and Castillo, Susana and Stiller, Sebastian and Magnor, Marcus},
title = {Shape From Caustics: Reconstruction of 3D-Printed Glass From Simulated Caustic Images},
booktitle = {Proceedings of the IEEE/CVF Winter Conferenc... | We present an efficient and effective computational framework for the inverse rendering problem of reconstructing the 3D shape of a piece of glass from its caustic image. Our approach is motivated by the needs of 3D glass printing, a nascent additive manufacturing technique that promises to revolutionize the production... |
Hwang_Weakly_Supervised_Instance_Segmentation_by_Deep_Community_Learning_WACV_2021_paper | Weakly Supervised Instance Segmentation by Deep Community Learning | [
"Jaedong Hwang",
"Seohyun Kim",
"Jeany Son",
"Bohyung Han"
] | https://openaccess.thecvf.com/content/WACV2021/html/Hwang_Weakly_Supervised_Instance_Segmentation_by_Deep_Community_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Hwang_Weakly_Supervised_Instance_Segmentation_by_Deep_Community_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Hwang_Weakly_Supervised_Instance_WACV_2021_supplemental.pdf | 2001.11207 | cvf | @InProceedings{Hwang_2021_WACV,
author = {Hwang, Jaedong and Kim, Seohyun and Son, Jeany and Han, Bohyung},
title = {Weakly Supervised Instance Segmentation by Deep Community Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | We present a weakly supervised instance segmentation algorithm based on deep community learning with multiple tasks. This task is formulated as a combination of weakly supervised object detection and semantic segmentation, where individual objects of the same class are identified and segmented separately. We address th... |
Chen_Coarse-to-Fine_Gaze_Redirection_With_Numerical_and_Pictorial_Guidance_WACV_2021_paper | Coarse-to-Fine Gaze Redirection With Numerical and Pictorial Guidance | [
"Jingjing Chen",
"Jichao Zhang",
"Enver Sangineto",
"Tao Chen",
"Jiayuan Fan",
"Nicu Sebe"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chen_Coarse-to-Fine_Gaze_Redirection_With_Numerical_and_Pictorial_Guidance_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chen_Coarse-to-Fine_Gaze_Redirection_With_Numerical_and_Pictorial_Guidance_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Chen_Coarse-to-Fine_Gaze_Redirection_WACV_2021_supplemental.pdf | 2004.03064 | cvf | @InProceedings{Chen_2021_WACV,
author = {Chen, Jingjing and Zhang, Jichao and Sangineto, Enver and Chen, Tao and Fan, Jiayuan and Sebe, Nicu},
title = {Coarse-to-Fine Gaze Redirection With Numerical and Pictorial Guidance},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of... | Gaze redirection aims at manipulating the gaze of a given face image with respect to a desired direction (i.e., a reference angle) and it can be applied to many real life scenarios, such as video-conferencing or taking group photos. However, previous work on this topic mainly suffers of two limitations: (1) Low-quality... |
Cheng_S3-Net_A_Fast_and_Lightweight_Video_Scene_Understanding_Network_by_WACV_2021_paper | S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-Shot Segmentation | [
"Yuan Cheng",
"Yuchao Yang",
"Hai-Bao Chen",
"Ngai Wong",
"Hao Yu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Cheng_S3-Net_A_Fast_and_Lightweight_Video_Scene_Understanding_Network_by_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Cheng_S3-Net_A_Fast_and_Lightweight_Video_Scene_Understanding_Network_by_WACV_2021_paper.pdf | null | 2011.02265 | title_snapshot | @InProceedings{Cheng_2021_WACV,
author = {Cheng, Yuan and Yang, Yuchao and Chen, Hai-Bao and Wong, Ngai and Yu, Hao},
title = {S3-Net: A Fast and Lightweight Video Scene Understanding Network by Single-Shot Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of C... | Real-time understanding in video is crucial in various AI applications such as autonomous driving. This work presents a fast single-shot segmentation strategy for video scene understanding. The proposed net, called S3-Net, quickly locates and segments target sub-scenes, meanwhile extracts structured time-series semanti... |
Kou_Improve_CAM_With_Auto-Adapted_Segmentation_and_Co-Supervised_Augmentation_WACV_2021_paper | Improve CAM With Auto-Adapted Segmentation and Co-Supervised Augmentation | [
"Ziyi Kou",
"Guofeng Cui",
"Shaojie Wang",
"Wentian Zhao",
"Chenliang Xu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kou_Improve_CAM_With_Auto-Adapted_Segmentation_and_Co-Supervised_Augmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kou_Improve_CAM_With_Auto-Adapted_Segmentation_and_Co-Supervised_Augmentation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kou_Improve_CAM_With_WACV_2021_supplemental.pdf | 1911.07160 | title_snapshot | @InProceedings{Kou_2021_WACV,
author = {Kou, Ziyi and Cui, Guofeng and Wang, Shaojie and Zhao, Wentian and Xu, Chenliang},
title = {Improve CAM With Auto-Adapted Segmentation and Co-Supervised Augmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision... | Weakly Supervised Object Localization (WSOL) methods generate both classification and localization results by learning from only image category labels. Previous methods usually utilize class activation map (CAM) to obtain target object regions. However, most of them only focus on improving foreground object parts in CA... |
Ding_Analyzing_Deep_Neural_Networks_Transferability_via_Frechet_Distance_WACV_2021_paper | Analyzing Deep Neural Network's Transferability via Frechet Distance | [
"Yifan Ding",
"Liqiang Wang",
"Boqing Gong"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ding_Analyzing_Deep_Neural_Networks_Transferability_via_Frechet_Distance_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ding_Analyzing_Deep_Neural_Networks_Transferability_via_Frechet_Distance_WACV_2021_paper.pdf | null | null | null | @InProceedings{Ding_2021_WACV,
author = {Ding, Yifan and Wang, Liqiang and Gong, Boqing},
title = {Analyzing Deep Neural Network's Transferability via Frechet Distance},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | Transfer learning has become the de facto practice to reuse a deep neural network (DNN) that is pre-trained with abundant training data in a source task to improve the model training on target tasks with smaller-scale training data. In this paper, we first investigate the correlation between the DNN's pre-training perf... |
Li_Controllable_and_Progressive_Image_Extrapolation_WACV_2021_paper | Controllable and Progressive Image Extrapolation | [
"Yijun Li",
"Lu Jiang",
"Ming-Hsuan Yang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Li_Controllable_and_Progressive_Image_Extrapolation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Li_Controllable_and_Progressive_Image_Extrapolation_WACV_2021_paper.pdf | null | 1912.11711 | cvf | @InProceedings{Li_2021_WACV,
author = {Li, Yijun and Jiang, Lu and Yang, Ming-Hsuan},
title = {Controllable and Progressive Image Extrapolation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
... | Image extrapolation aims at expanding the narrow field of view of a given image patch. Existing models mainly deal with natural scene images of homogeneous regions and have no control of the content generation process. In this work, we study conditional image extrapolation to synthesize new images guided by the input s... |
Wang_How_to_Make_a_BLT_Sandwich_Learning_VQA_Towards_Understanding_WACV_2021_paper | How to Make a BLT Sandwich? Learning VQA Towards Understanding Web Instructional Videos | [
"Shaojie Wang",
"Wentian Zhao",
"Ziyi Kou",
"Jing Shi",
"Chenliang Xu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wang_How_to_Make_a_BLT_Sandwich_Learning_VQA_Towards_Understanding_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wang_How_to_Make_a_BLT_Sandwich_Learning_VQA_Towards_Understanding_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Wang_How_to_Make_WACV_2021_supplemental.zip | 1812.00344 | title_judge | @InProceedings{Wang_2021_WACV,
author = {Wang, Shaojie and Zhao, Wentian and Kou, Ziyi and Shi, Jing and Xu, Chenliang},
title = {How to Make a BLT Sandwich? Learning VQA Towards Understanding Web Instructional Videos},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Com... | Understanding web instructional videos is an essential branch of video understanding in two aspects. First, most existing video methods focus on short-term actions for a-few-second-long video clips; these methods are not directly applicable to long videos. Second, unlike unconstrained long videos, e.g., movies, instruc... |
Tang_Proposal_Learning_for_Semi-Supervised_Object_Detection_WACV_2021_paper | Proposal Learning for Semi-Supervised Object Detection | [
"Peng Tang",
"Chetan Ramaiah",
"Yan Wang",
"Ran Xu",
"Caiming Xiong"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tang_Proposal_Learning_for_Semi-Supervised_Object_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tang_Proposal_Learning_for_Semi-Supervised_Object_Detection_WACV_2021_paper.pdf | null | 2001.05086 | cvf | @InProceedings{Tang_2021_WACV,
author = {Tang, Peng and Ramaiah, Chetan and Wang, Yan and Xu, Ran and Xiong, Caiming},
title = {Proposal Learning for Semi-Supervised Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | In this paper, we focus on semi-supervised object detection to boost performance of proposal-based object detectors (a.k.a. two-stage object detectors) by training on both labeled and unlabeled data. However, it is non-trivial to train object detectors on unlabeled data due to the unavailability of ground truth labels.... |
Wang_Multi-Path_Neural_Networks_for_On-Device_Multi-Domain_Visual_Classification_WACV_2021_paper | Multi-Path Neural Networks for On-Device Multi-Domain Visual Classification | [
"Qifei Wang",
"Junjie Ke",
"Joshua Greaves",
"Grace Chu",
"Gabriel Bender",
"Luciano Sbaiz",
"Alec Go",
"Andrew Howard",
"Ming-Hsuan Yang",
"Jeff Gilbert",
"Peyman Milanfar",
"Feng Yang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wang_Multi-Path_Neural_Networks_for_On-Device_Multi-Domain_Visual_Classification_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wang_Multi-Path_Neural_Networks_for_On-Device_Multi-Domain_Visual_Classification_WACV_2021_paper.pdf | null | 2010.04904 | cvf | @InProceedings{Wang_2021_WACV,
author = {Wang, Qifei and Ke, Junjie and Greaves, Joshua and Chu, Grace and Bender, Gabriel and Sbaiz, Luciano and Go, Alec and Howard, Andrew and Yang, Ming-Hsuan and Gilbert, Jeff and Milanfar, Peyman and Yang, Feng},
title = {Multi-Path Neural Networks for On-Device Mult... | Learning multiple domains/tasks with a single model is important for improving data efficiency and lowering inference cost for numerous vision tasks, especially on resource-constrained mobile devices. However, hand-crafting a multi-domain/task model can be both tedious and challenging. This paper proposes a novel appro... |
Nayak_Effectiveness_of_Arbitrary_Transfer_Sets_for_Data-Free_Knowledge_Distillation_WACV_2021_paper | Effectiveness of Arbitrary Transfer Sets for Data-Free Knowledge Distillation | [
"Gaurav Kumar Nayak",
"Konda Reddy Mopuri",
"Anirban Chakraborty"
] | https://openaccess.thecvf.com/content/WACV2021/html/Nayak_Effectiveness_of_Arbitrary_Transfer_Sets_for_Data-Free_Knowledge_Distillation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Nayak_Effectiveness_of_Arbitrary_Transfer_Sets_for_Data-Free_Knowledge_Distillation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Nayak_Effectiveness_of_Arbitrary_WACV_2021_supplemental.pdf | 2011.09113 | cvf | @InProceedings{Nayak_2021_WACV,
author = {Nayak, Gaurav Kumar and Mopuri, Konda Reddy and Chakraborty, Anirban},
title = {Effectiveness of Arbitrary Transfer Sets for Data-Free Knowledge Distillation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV... | Knowledge Distillation is an effective method to transfer the learning across deep neural networks. Typically, the dataset originally used for training the Teacher model is chosen as the "Transfer Set" to conduct the knowledge transfer to the Student. However, this original training data may not always be freely availa... |
Liu_Relighting_Images_in_the_Wild_With_a_Self-Supervised_Siamese_Auto-Encoder_WACV_2021_paper | Relighting Images in the Wild With a Self-Supervised Siamese Auto-Encoder | [
"Yang Liu",
"Alexandros Neophytou",
"Sunando Sengupta",
"Eric Sommerlade"
] | https://openaccess.thecvf.com/content/WACV2021/html/Liu_Relighting_Images_in_the_Wild_With_a_Self-Supervised_Siamese_Auto-Encoder_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Liu_Relighting_Images_in_the_Wild_With_a_Self-Supervised_Siamese_Auto-Encoder_WACV_2021_paper.pdf | null | 2012.06444 | cvf | @InProceedings{Liu_2021_WACV,
author = {Liu, Yang and Neophytou, Alexandros and Sengupta, Sunando and Sommerlade, Eric},
title = {Relighting Images in the Wild With a Self-Supervised Siamese Auto-Encoder},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (... | We propose a self-supervised method for image relighting of single view images in the wild. The method is based on an auto-encoder which deconstructs an image into two separate encodings, relating to the scene illumination and content. In order to disentangle this embedding information without supervision, we exploit t... |
Lin_Attention-Based_Spatial_Guidance_for_Image-to-Image_Translation_WACV_2021_paper | Attention-Based Spatial Guidance for Image-to-Image Translation | [
"Yu Lin",
"Yigong Wang",
"Yifan Li",
"Yang Gao",
"Zhuoyi Wang",
"Latifur Khan"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lin_Attention-Based_Spatial_Guidance_for_Image-to-Image_Translation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lin_Attention-Based_Spatial_Guidance_for_Image-to-Image_Translation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Lin_Attention-Based_Spatial_Guidance_WACV_2021_supplemental.pdf | null | null | @InProceedings{Lin_2021_WACV,
author = {Lin, Yu and Wang, Yigong and Li, Yifan and Gao, Yang and Wang, Zhuoyi and Khan, Latifur},
title = {Attention-Based Spatial Guidance for Image-to-Image Translation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | The aim of image-to-image translation algorithms is to tackle the challenges of learning a proper mapping function across different domains. Generative Adversarial Networks (GAN) have shown superior ability to handle this problem by both supervised and unsupervised ways. However, one critical problem of GAN in practice... |
Oh_EVET_Enhancing_Visual_Explanations_of_Deep_Neural_Networks_Using_Image_WACV_2021_paper | EVET: Enhancing Visual Explanations of Deep Neural Networks Using Image Transformations | [
"Youngrock Oh",
"Hyungsik Jung",
"Jeonghyung Park",
"Min Soo Kim"
] | https://openaccess.thecvf.com/content/WACV2021/html/Oh_EVET_Enhancing_Visual_Explanations_of_Deep_Neural_Networks_Using_Image_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Oh_EVET_Enhancing_Visual_Explanations_of_Deep_Neural_Networks_Using_Image_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Oh_EVET_Enhancing_Visual_WACV_2021_supplemental.pdf | null | null | @InProceedings{Oh_2021_WACV,
author = {Oh, Youngrock and Jung, Hyungsik and Park, Jeonghyung and Kim, Min Soo},
title = {EVET: Enhancing Visual Explanations of Deep Neural Networks Using Image Transformations},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vis... | Numerous interpretability methods have been developed to visually explain the behavior of complex machine learning models by estimating parts of the input image that are critical for the model's prediction. We propose a general pipeline of enhancing visual explanations using image transformations (EVET). EVET considers... |
Kang_ATM_Attentional_Text_Matting_WACV_2021_paper | ATM: Attentional Text Matting | [
"Peng Kang",
"Jianping Zhang",
"Chen Ma",
"Guiling Sun"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kang_ATM_Attentional_Text_Matting_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kang_ATM_Attentional_Text_Matting_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kang_ATM_Attentional_Text_WACV_2021_supplemental.pdf | null | null | @InProceedings{Kang_2021_WACV,
author = {Kang, Peng and Zhang, Jianping and Ma, Chen and Sun, Guiling},
title = {ATM: Attentional Text Matting},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
... | Image matting is a fundamental computer vision problem and has many applications. Previous image matting methods always focus on extracting a general object or portrait from the background in an image. In this paper, we try to solve the text matting problem, which extracts characters (usually WordArts) from the backgro... |
Ornhag_Efficient_Real-Time_Radial_Distortion_Correction_for_UAVs_WACV_2021_paper | Efficient Real-Time Radial Distortion Correction for UAVs | [
"Marcus Valtonen Ornhag",
"Patrik Persson",
"Marten Wadenback",
"Kalle Astrom",
"Anders Heyden"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ornhag_Efficient_Real-Time_Radial_Distortion_Correction_for_UAVs_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ornhag_Efficient_Real-Time_Radial_Distortion_Correction_for_UAVs_WACV_2021_paper.pdf | null | 2010.04203 | cvf | @InProceedings{Ornhag_2021_WACV,
author = {Ornhag, Marcus Valtonen and Persson, Patrik and Wadenback, Marten and Astrom, Kalle and Heyden, Anders},
title = {Efficient Real-Time Radial Distortion Correction for UAVs},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comput... | In this paper we present a novel algorithm for onboard radial distortion correction for unmanned aerial vehicles (UAVs) equipped with an inertial measurement unit (IMU), that runs in real-time. This approach makes calibration procedures redundant, thus allowing for exchange of optics extemporaneously. By utilizing the ... |
Niklaus_Learned_Dual-View_Reflection_Removal_WACV_2021_paper | Learned Dual-View Reflection Removal | [
"Simon Niklaus",
"Xuaner (Cecilia) Zhang",
"Jonathan T. Barron",
"Neal Wadhwa",
"Rahul Garg",
"Feng Liu",
"Tianfan Xue"
] | https://openaccess.thecvf.com/content/WACV2021/html/Niklaus_Learned_Dual-View_Reflection_Removal_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Niklaus_Learned_Dual-View_Reflection_Removal_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Niklaus_Learned_Dual-View_Reflection_WACV_2021_supplemental.pdf | 2010.00702 | cvf | @InProceedings{Niklaus_2021_WACV,
author = {Niklaus, Simon and Zhang, Xuaner (Cecilia) and Barron, Jonathan T. and Wadhwa, Neal and Garg, Rahul and Liu, Feng and Xue, Tianfan},
title = {Learned Dual-View Reflection Removal},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications o... | Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconvenient for users. We instead propose a learning-based dereflection algorithm that uses stereo images as input. This is an effective trade-of... |
Tran_Goal-Driven_Long-Term_Trajectory_Prediction_WACV_2021_paper | Goal-Driven Long-Term Trajectory Prediction | [
"Hung Tran",
"Vuong Le",
"Truyen Tran"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tran_Goal-Driven_Long-Term_Trajectory_Prediction_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tran_Goal-Driven_Long-Term_Trajectory_Prediction_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Tran_Goal-Driven_Long-Term_Trajectory_WACV_2021_supplemental.zip | 2011.02751 | cvf | @InProceedings{Tran_2021_WACV,
author = {Tran, Hung and Le, Vuong and Tran, Truyen},
title = {Goal-Driven Long-Term Trajectory Prediction},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pag... | The prediction of humans' short-term trajectories has advanced significantly with the use of powerful sequential modeling and rich environment feature extraction. However, long-term prediction is still a major challenge for the current methods as the errors could accumulate along the way. Indeed, consistent and stable ... |
Jing_VideoSSL_Semi-Supervised_Learning_for_Video_Classification_WACV_2021_paper | VideoSSL: Semi-Supervised Learning for Video Classification | [
"Longlong Jing",
"Toufiq Parag",
"Zhe Wu",
"Yingli Tian",
"Hongcheng Wang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Jing_VideoSSL_Semi-Supervised_Learning_for_Video_Classification_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Jing_VideoSSL_Semi-Supervised_Learning_for_Video_Classification_WACV_2021_paper.pdf | null | 2003.00197 | cvf | @InProceedings{Jing_2021_WACV,
author = {Jing, Longlong and Parag, Toufiq and Wu, Zhe and Tian, Yingli and Wang, Hongcheng},
title = {VideoSSL: Semi-Supervised Learning for Video Classification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | We propose a semi-supervised learning approach for video classification, VideoSSL, using convolutional neural networks (CNN). Like other computer vision tasks, existing supervised video classification methods demand a large amount of labeled data to attain good performance. However, annotation of a large dataset is exp... |
Soleymani_Mutual_Information_Maximization_on_Disentangled_Representations_for_Differential_Morph_Detection_WACV_2021_paper | Mutual Information Maximization on Disentangled Representations for Differential Morph Detection | [
"Sobhan Soleymani",
"Ali Dabouei",
"Fariborz Taherkhani",
"Jeremy Dawson",
"Nasser M. Nasrabadi"
] | https://openaccess.thecvf.com/content/WACV2021/html/Soleymani_Mutual_Information_Maximization_on_Disentangled_Representations_for_Differential_Morph_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Soleymani_Mutual_Information_Maximization_on_Disentangled_Representations_for_Differential_Morph_Detection_WACV_2021_paper.pdf | null | 2012.01542 | cvf | @InProceedings{Soleymani_2021_WACV,
author = {Soleymani, Sobhan and Dabouei, Ali and Taherkhani, Fariborz and Dawson, Jeremy and Nasrabadi, Nasser M.},
title = {Mutual Information Maximization on Disentangled Representations for Differential Morph Detection},
booktitle = {Proceedings of the IEEE/CVF ... | In this paper, we present a novel differential morph detection framework, utilizing landmark and appearance disentanglement. In our framework, the face image is represented in the embedding domain using two disentangled but complementary representations. The network is trained by triplets of face images, in which the i... |
Luo_Few-Shot_Learning_via_Feature_Hallucination_With_Variational_Inference_WACV_2021_paper | Few-Shot Learning via Feature Hallucination With Variational Inference | [
"Qinxuan Luo",
"Lingfeng Wang",
"Jingguo Lv",
"Shiming Xiang",
"Chunhong Pan"
] | https://openaccess.thecvf.com/content/WACV2021/html/Luo_Few-Shot_Learning_via_Feature_Hallucination_With_Variational_Inference_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Luo_Few-Shot_Learning_via_Feature_Hallucination_With_Variational_Inference_WACV_2021_paper.pdf | null | null | null | @InProceedings{Luo_2021_WACV,
author = {Luo, Qinxuan and Wang, Lingfeng and Lv, Jingguo and Xiang, Shiming and Pan, Chunhong},
title = {Few-Shot Learning via Feature Hallucination With Variational Inference},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Visio... | Deep learning has achieved huge success in the field of artificial intelligence, but the performance heavily depends on labeled data. Few-shot learning aims to make a model rapidly adapt to unseen classes with few labeled samples after training on a base dataset, and this is useful for tasks lacking labeled data such a... |
Zhang_Line_Art_Correlation_Matching_Feature_Transfer_Network_for_Automatic_Animation_WACV_2021_paper | Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization | [
"Qian Zhang",
"Bo Wang",
"Wei Wen",
"Hai Li",
"Junhui Liu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Line_Art_Correlation_Matching_Feature_Transfer_Network_for_Automatic_Animation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Line_Art_Correlation_Matching_Feature_Transfer_Network_for_Automatic_Animation_WACV_2021_paper.pdf | null | 2004.06718 | cvf | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Qian and Wang, Bo and Wen, Wei and Li, Hai and Liu, Junhui},
title = {Line Art Correlation Matching Feature Transfer Network for Automatic Animation Colorization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer V... | Automatic animation line art colorization is a challenging computer vision problem, since the information of the line art is highly sparse and abstracted and there exists a strict requirement for the color and style consistency between frames. Recently, a lot of Generative Adversarial Network (GAN) based image-to-image... |
Seets_Motion_Adaptive_Deblurring_With_Single-Photon_Cameras_WACV_2021_paper | Motion Adaptive Deblurring With Single-Photon Cameras | [
"Trevor Seets",
"Atul Ingle",
"Martin Laurenzis",
"Andreas Velten"
] | https://openaccess.thecvf.com/content/WACV2021/html/Seets_Motion_Adaptive_Deblurring_With_Single-Photon_Cameras_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Seets_Motion_Adaptive_Deblurring_With_Single-Photon_Cameras_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Seets_Motion_Adaptive_Deblurring_WACV_2021_supplemental.zip | 2012.07931 | cvf | @InProceedings{Seets_2021_WACV,
author = {Seets, Trevor and Ingle, Atul and Laurenzis, Martin and Velten, Andreas},
title = {Motion Adaptive Deblurring With Single-Photon Cameras},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {... | Single-photon avalanche diodes (SPADs) are a rapidly developing image sensing technology with extreme low-light sensitivity and picosecond timing resolution. These unique capabilities have enabled SPADs to be used in applications like LiDAR, non-line-of-sight imaging and fluorescence microscopy that require imaging in ... |
Benz_Revisiting_Batch_Normalization_for_Improving_Corruption_Robustness_WACV_2021_paper | Revisiting Batch Normalization for Improving Corruption Robustness | [
"Philipp Benz",
"Chaoning Zhang",
"Adil Karjauv",
"In So Kweon"
] | https://openaccess.thecvf.com/content/WACV2021/html/Benz_Revisiting_Batch_Normalization_for_Improving_Corruption_Robustness_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Benz_Revisiting_Batch_Normalization_for_Improving_Corruption_Robustness_WACV_2021_paper.pdf | null | 2010.03630 | cvf | @InProceedings{Benz_2021_WACV,
author = {Benz, Philipp and Zhang, Chaoning and Karjauv, Adil and Kweon, In So},
title = {Revisiting Batch Normalization for Improving Corruption Robustness},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mont... | The performance of DNNs trained on clean images has been shown to decrease when the test images have common corruptions. In this work, we interpret corruption robustness as a domain shift and propose to rectify batch normalization (BN) statistics for improving model robustness. This is motivated by perceiving the shift... |
Park_Adaptive_Streaming_of_360-Degree_Videos_With_Reinforcement_Learning_WACV_2021_paper | Adaptive Streaming of 360-Degree Videos With Reinforcement Learning | [
"Sohee Park",
"Minh Hoai",
"Arani Bhattacharya",
"Samir R. Das"
] | https://openaccess.thecvf.com/content/WACV2021/html/Park_Adaptive_Streaming_of_360-Degree_Videos_With_Reinforcement_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Park_Adaptive_Streaming_of_360-Degree_Videos_With_Reinforcement_Learning_WACV_2021_paper.pdf | null | null | null | @InProceedings{Park_2021_WACV,
author = {Park, Sohee and Hoai, Minh and Bhattacharya, Arani and Das, Samir R.},
title = {Adaptive Streaming of 360-Degree Videos With Reinforcement Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mon... | For bandwidth-efficient streaming of 360-degree videos, the streaming technique must adapt both to the changing viewport of the user and variations of the available network bandwidth. The state-of-the-art streaming techniques for this problem attempt to solve an optimization using simplified rules that do not adapt ver... |
Zhang_Automatic_Calibration_of_the_Fisheye_Camera_for_Egocentric_3D_Human_WACV_2021_paper | Automatic Calibration of the Fisheye Camera for Egocentric 3D Human Pose Estimation From a Single Image | [
"Yahui Zhang",
"Shaodi You",
"Theo Gevers"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Automatic_Calibration_of_the_Fisheye_Camera_for_Egocentric_3D_Human_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Automatic_Calibration_of_the_Fisheye_Camera_for_Egocentric_3D_Human_WACV_2021_paper.pdf | null | null | null | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Yahui and You, Shaodi and Gevers, Theo},
title = {Automatic Calibration of the Fisheye Camera for Egocentric 3D Human Pose Estimation From a Single Image},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | We propose a method for egocentric 3D human pose estimation from a single image captured by a fisheye camera. The problem of estimating the egocentric 3D pose for a fisheye camera is that images may be subject to strong image distortions (e.g. 2D poses on the image plane that pass through the line of sight of the fishe... |
Chandhok_Two-Level_Adversarial_Visual-Semantic_Coupling_for_Generalized_Zero-Shot_Learning_WACV_2021_paper | Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-Shot Learning | [
"Shivam Chandhok",
"Vineeth N Balasubramanian"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chandhok_Two-Level_Adversarial_Visual-Semantic_Coupling_for_Generalized_Zero-Shot_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chandhok_Two-Level_Adversarial_Visual-Semantic_Coupling_for_Generalized_Zero-Shot_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Chandhok_Two-Level_Adversarial_Visual-Semantic_WACV_2021_supplemental.pdf | 2007.07757 | cvf | @InProceedings{Chandhok_2021_WACV,
author = {Chandhok, Shivam and Balasubramanian, Vineeth N},
title = {Two-Level Adversarial Visual-Semantic Coupling for Generalized Zero-Shot Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | The performance of generative zero-shot methods mainly depends on the quality of generated features and how well the model facilitates knowledge transfer between visual and semantic domains. The quality of generated features is a direct consequence of the ability of the model to capture the several modes of the underly... |
Toldo_Unsupervised_Domain_Adaptation_in_Semantic_Segmentation_via_Orthogonal_and_Clustered_WACV_2021_paper | Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings | [
"Marco Toldo",
"Umberto Michieli",
"Pietro Zanuttigh"
] | https://openaccess.thecvf.com/content/WACV2021/html/Toldo_Unsupervised_Domain_Adaptation_in_Semantic_Segmentation_via_Orthogonal_and_Clustered_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Toldo_Unsupervised_Domain_Adaptation_in_Semantic_Segmentation_via_Orthogonal_and_Clustered_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Toldo_Unsupervised_Domain_Adaptation_WACV_2021_supplemental.pdf | 2011.12616 | cvf | @InProceedings{Toldo_2021_WACV,
author = {Toldo, Marco and Michieli, Umberto and Zanuttigh, Pietro},
title = {Unsupervised Domain Adaptation in Semantic Segmentation via Orthogonal and Clustered Embeddings},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision... | Deep learning frameworks allowed for a remarkable advancement in semantic segmentation, but the data hungry nature of convolutional networks has rapidly raised the demand for adaptation techniques able to transfer learned knowledge from label-abundant domains to unlabeled ones. In this paper we propose an effective Uns... |
Patel_Saliency_Driven_Perceptual_Image_Compression_WACV_2021_paper | Saliency Driven Perceptual Image Compression | [
"Yash Patel",
"Srikar Appalaraju",
"R. Manmatha"
] | https://openaccess.thecvf.com/content/WACV2021/html/Patel_Saliency_Driven_Perceptual_Image_Compression_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Patel_Saliency_Driven_Perceptual_Image_Compression_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Patel_Saliency_Driven_Perceptual_WACV_2021_supplemental.pdf | 2002.04988 | cvf | @InProceedings{Patel_2021_WACV,
author = {Patel, Yash and Appalaraju, Srikar and Manmatha, R.},
title = {Saliency Driven Perceptual Image Compression},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {20... | This paper proposes a new end-to-end trainable model for lossy image compression, which includes several novel components. The method incorporates 1) an adequate perceptual similarity metric; 2) saliency in the images; 3) a hierarchical auto-regressive model. This paper demonstrates that the popularly used evaluations ... |
Parsa_A_Multi-Task_Learning_Approach_for_Human_Activity_Segmentation_and_Ergonomics_WACV_2021_paper | A Multi-Task Learning Approach for Human Activity Segmentation and Ergonomics Risk Assessment | [
"Behnoosh Parsa",
"Ashis G. Banerjee"
] | https://openaccess.thecvf.com/content/WACV2021/html/Parsa_A_Multi-Task_Learning_Approach_for_Human_Activity_Segmentation_and_Ergonomics_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Parsa_A_Multi-Task_Learning_Approach_for_Human_Activity_Segmentation_and_Ergonomics_WACV_2021_paper.pdf | null | 2008.03014 | cvf | @InProceedings{Parsa_2021_WACV,
author = {Parsa, Behnoosh and Banerjee, Ashis G.},
title = {A Multi-Task Learning Approach for Human Activity Segmentation and Ergonomics Risk Assessment},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | We propose a new approach to Human Activity Evaluation (HAE) in long videos using graph-based multi-task modeling. Previous works in activity evaluation either directly compute a metric using a detected skeleton or use the scene information to regress the activity score. These approaches are insufficient for accurate a... |
Srivastava_A_Variational_Information_Bottleneck_Based_Method_to_Compress_Sequential_Networks_WACV_2021_paper | A Variational Information Bottleneck Based Method to Compress Sequential Networks for Human Action Recognition | [
"Ayush Srivastava",
"Oshin Dutta",
"Jigyasa Gupta",
"Sumeet Agarwal",
"Prathosh AP"
] | https://openaccess.thecvf.com/content/WACV2021/html/Srivastava_A_Variational_Information_Bottleneck_Based_Method_to_Compress_Sequential_Networks_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Srivastava_A_Variational_Information_Bottleneck_Based_Method_to_Compress_Sequential_Networks_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Srivastava_A_Variational_Information_WACV_2021_supplemental.pdf | 2010.01343 | cvf | @InProceedings{Srivastava_2021_WACV,
author = {Srivastava, Ayush and Dutta, Oshin and Gupta, Jigyasa and Agarwal, Sumeet and AP, Prathosh},
title = {A Variational Information Bottleneck Based Method to Compress Sequential Networks for Human Action Recognition},
booktitle = {Proceedings of the IEEE/CV... | In the last few years, deep neural networks' compression has become an important strand of machine learning and computer vision research. Deep models require sizeable computational complexity and storage when used, for instance, for Human Action Recognition (HAR) from videos, making them unsuitable to be deployed on ed... |
Zhang_Adversarial_Reinforcement_Learning_for_Unsupervised_Domain_Adaptation_WACV_2021_paper | Adversarial Reinforcement Learning for Unsupervised Domain Adaptation | [
"Youshan Zhang",
"Hui Ye",
"Brian D. Davison"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Adversarial_Reinforcement_Learning_for_Unsupervised_Domain_Adaptation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Adversarial_Reinforcement_Learning_for_Unsupervised_Domain_Adaptation_WACV_2021_paper.pdf | null | null | null | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Youshan and Ye, Hui and Davison, Brian D.},
title = {Adversarial Reinforcement Learning for Unsupervised Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January... | Transferring knowledge from an existing labeled domain to a new domain often suffers from domain shift in which performance degrades because of differences between the domains. Domain adaptation has been a prominent method to mitigate such a problem. There have been many pre-trained neural networks for feature extracti... |
Nie_A_Robust_and_Efficient_Framework_for_Sports-Field_Registration_WACV_2021_paper | A Robust and Efficient Framework for Sports-Field Registration | [
"Xiaohan Nie",
"Shixing Chen",
"Raffay Hamid"
] | https://openaccess.thecvf.com/content/WACV2021/html/Nie_A_Robust_and_Efficient_Framework_for_Sports-Field_Registration_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Nie_A_Robust_and_Efficient_Framework_for_Sports-Field_Registration_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Nie_A_Robust_and_WACV_2021_supplemental.zip | null | null | @InProceedings{Nie_2021_WACV,
author = {Nie, Xiaohan and Chen, Shixing and Hamid, Raffay},
title = {A Robust and Efficient Framework for Sports-Field Registration},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
ye... | We propose a novel framework to register sports-fields as they appear in broadcast sports videos. Unlike previous approaches, we particularly address the challenge of field-registration when: (a) there are not enough distinguishable features on the field, and (b) no prior knowledge is available about the camera. To thi... |
Rego_Robust_Lensless_Image_Reconstruction_via_PSF_Estimation_WACV_2021_paper | Robust Lensless Image Reconstruction via PSF Estimation | [
"Joshua D. Rego",
"Karthik Kulkarni",
"Suren Jayasuriya"
] | https://openaccess.thecvf.com/content/WACV2021/html/Rego_Robust_Lensless_Image_Reconstruction_via_PSF_Estimation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Rego_Robust_Lensless_Image_Reconstruction_via_PSF_Estimation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Rego_Robust_Lensless_Image_WACV_2021_supplemental.pdf | null | null | @InProceedings{Rego_2021_WACV,
author = {Rego, Joshua D. and Kulkarni, Karthik and Jayasuriya, Suren},
title = {Robust Lensless Image Reconstruction via PSF Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | Lensless imaging is a new, emerging modality where image sensors utilize optical elements in front of the sensor to perform multiplexed imaging. There have been several recent papers to reconstruct images from lensless imagers, including methods that utilize deep learning for state-of-the-art performance. However, many... |
Yin_Person-in-Context_Synthesis_With_Compositional_Structural_Space_WACV_2021_paper | Person-in-Context Synthesis With Compositional Structural Space | [
"Weidong Yin",
"Ziwei Liu",
"Leonid Sigal"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yin_Person-in-Context_Synthesis_With_Compositional_Structural_Space_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yin_Person-in-Context_Synthesis_With_Compositional_Structural_Space_WACV_2021_paper.pdf | null | 2008.12679 | title_judge | @InProceedings{Yin_2021_WACV,
author = {Yin, Weidong and Liu, Ziwei and Sigal, Leonid},
title = {Person-in-Context Synthesis With Compositional Structural Space},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year... | Despite significant progress, controlled generation of complex images with interacting people remains difficult. Existing layout generation methods fall short of synthesizing realistic person instances; while pose-guided generation approaches focus on a single person and assume simple or known backgrounds. To tackle th... |
Mercier_Deep_Template-Based_Object_Instance_Detection_WACV_2021_paper | Deep Template-Based Object Instance Detection | [
"Jean-Philippe Mercier",
"Mathieu Garon",
"Philippe Giguere",
"Jean-Francois Lalonde"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mercier_Deep_Template-Based_Object_Instance_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mercier_Deep_Template-Based_Object_Instance_Detection_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Mercier_Deep_Template-Based_Object_WACV_2021_supplemental.pdf | 1911.11822 | cvf | @InProceedings{Mercier_2021_WACV,
author = {Mercier, Jean-Philippe and Garon, Mathieu and Giguere, Philippe and Lalonde, Jean-Francois},
title = {Deep Template-Based Object Instance Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Much of the focus in the object detection literature has been on the problem of identifying the bounding box of a particular class of object in an image. Yet, in contexts such as robotics and augmented reality, it is often necessary to find a specific object instance--a unique toy or a custom industrial part for exampl... |
Ke_Future_Moment_Assessment_for_Action_Query_WACV_2021_paper | Future Moment Assessment for Action Query | [
"Qiuhong Ke",
"Mario Fritz",
"Bernt Schiele"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ke_Future_Moment_Assessment_for_Action_Query_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ke_Future_Moment_Assessment_for_Action_Query_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Ke_Future_Moment_Assessment_WACV_2021_supplemental.pdf | null | null | @InProceedings{Ke_2021_WACV,
author = {Ke, Qiuhong and Fritz, Mario and Schiele, Bernt},
title = {Future Moment Assessment for Action Query},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
p... | In this paper, we aim to tackle the task of Assessing Future Moment of an Action of Interest (AFM-AI). The goal of this task is to assess if an action of interest will happen or not as well as the starting moment of the action. We aim to assess starting moments at any time-horizon of the future. To this end, we tackle ... |
Qian_Fast_Fourier_Intrinsic_Network_WACV_2021_paper | Fast Fourier Intrinsic Network | [
"Yanlin Qian",
"Miaojing Shi",
"Joni-Kristian Kamarainen",
"Jiri Matas"
] | https://openaccess.thecvf.com/content/WACV2021/html/Qian_Fast_Fourier_Intrinsic_Network_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Qian_Fast_Fourier_Intrinsic_Network_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Qian_Fast_Fourier_Intrinsic_WACV_2021_supplemental.pdf | 2011.04612 | cvf | @InProceedings{Qian_2021_WACV,
author = {Qian, Yanlin and Shi, Miaojing and Kamarainen, Joni-Kristian and Matas, Jiri},
title = {Fast Fourier Intrinsic Network},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | We address the problem of decomposing an image into albedo and shading. We propose the Fast Fourier Intrinsic Network, FFI-Net in short, that operates in the spectral domain, splitting the input into several spectral bands. Weights in FFI-Net are optimized in the spectral domain, allowing faster convergence to a lower ... |
Mathis_Pretraining_Boosts_Out-of-Domain_Robustness_for_Pose_Estimation_WACV_2021_paper | Pretraining Boosts Out-of-Domain Robustness for Pose Estimation | [
"Alexander Mathis",
"Thomas Biasi",
"Steffen Schneider",
"Mert Yuksekgonul",
"Byron Rogers",
"Matthias Bethge",
"Mackenzie W. Mathis"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mathis_Pretraining_Boosts_Out-of-Domain_Robustness_for_Pose_Estimation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mathis_Pretraining_Boosts_Out-of-Domain_Robustness_for_Pose_Estimation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Mathis_Pretraining_Boosts_Out-of-Domain_WACV_2021_supplemental.pdf | 1909.11229 | cvf | @InProceedings{Mathis_2021_WACV,
author = {Mathis, Alexander and Biasi, Thomas and Schneider, Steffen and Yuksekgonul, Mert and Rogers, Byron and Bethge, Matthias and Mathis, Mackenzie W.},
title = {Pretraining Boosts Out-of-Domain Robustness for Pose Estimation},
booktitle = {Proceedings of the IEEE... | Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe the generalization ability with three architecture classes (Mob... |
Rana_We_Dont_Need_Thousand_Proposals_Single_Shot_Actor-Action_Detection_in_WACV_2021_paper | We Don't Need Thousand Proposals: Single Shot Actor-Action Detection in Videos | [
"Aayush J. Rana",
"Yogesh S. Rawat"
] | https://openaccess.thecvf.com/content/WACV2021/html/Rana_We_Dont_Need_Thousand_Proposals_Single_Shot_Actor-Action_Detection_in_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Rana_We_Dont_Need_Thousand_Proposals_Single_Shot_Actor-Action_Detection_in_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Rana_We_Dont_Need_WACV_2021_supplemental.pdf | 2011.10927 | title_snapshot | @InProceedings{Rana_2021_WACV,
author = {Rana, Aayush J. and Rawat, Yogesh S.},
title = {We Don't Need Thousand Proposals: Single Shot Actor-Action Detection in Videos},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | We propose SSA2D, a simple yet effective end-to-end deep network for actor-action detection in videos. The existing methods take a top-down approach based on region-proposals (RPN), where the action is estimated based on the detected proposals followed by post-processing such as non-maximal suppression. While effective... |
Shafaei_AutoRetouch_Automatic_Professional_Face_Retouching_WACV_2021_paper | AutoRetouch: Automatic Professional Face Retouching | [
"Alireza Shafaei",
"James J. Little",
"Mark Schmidt"
] | https://openaccess.thecvf.com/content/WACV2021/html/Shafaei_AutoRetouch_Automatic_Professional_Face_Retouching_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Shafaei_AutoRetouch_Automatic_Professional_Face_Retouching_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Shafaei_AutoRetouch_Automatic_Professional_WACV_2021_supplemental.pdf | null | null | @InProceedings{Shafaei_2021_WACV,
author = {Shafaei, Alireza and Little, James J. and Schmidt, Mark},
title = {AutoRetouch: Automatic Professional Face Retouching},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
ye... | Face retouching is one of the most time-consuming steps in professional photography pipelines. The existing automated approaches blindly apply smoothing on the skin, destroying the delicate texture of the face. We present the first automatic face retouching approach that produces high-quality professional-grade results... |
Chen_Hierarchical_Generative_Adversarial_Networks_for_Single_Image_Super-Resolution_WACV_2021_paper | Hierarchical Generative Adversarial Networks for Single Image Super-Resolution | [
"Weimin Chen",
"Yuqing Ma",
"Xianglong Liu",
"Yi Yuan"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chen_Hierarchical_Generative_Adversarial_Networks_for_Single_Image_Super-Resolution_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chen_Hierarchical_Generative_Adversarial_Networks_for_Single_Image_Super-Resolution_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Chen_Hierarchical_Generative_Adversarial_WACV_2021_supplemental.pdf | null | null | @InProceedings{Chen_2021_WACV,
author = {Chen, Weimin and Ma, Yuqing and Liu, Xianglong and Yuan, Yi},
title = {Hierarchical Generative Adversarial Networks for Single Image Super-Resolution},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
m... | Recently, deep convolutional neural network (CNN) have achieved promising performance for single image super-resolution (SISR). However, they usually extract features on a single scale and lack sufficient supervision information, leading to undesired artifacts and unpleasant noise in super-resolution (SR) images. To ad... |
Koh_Text-to-Image_Generation_Grounded_by_Fine-Grained_User_Attention_WACV_2021_paper | Text-to-Image Generation Grounded by Fine-Grained User Attention | [
"Jing Yu Koh",
"Jason Baldridge",
"Honglak Lee",
"Yinfei Yang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Koh_Text-to-Image_Generation_Grounded_by_Fine-Grained_User_Attention_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Koh_Text-to-Image_Generation_Grounded_by_Fine-Grained_User_Attention_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Koh_Text-to-Image_Generation_Grounded_WACV_2021_supplemental.pdf | 2011.03775 | cvf | @InProceedings{Koh_2021_WACV,
author = {Koh, Jing Yu and Baldridge, Jason and Lee, Honglak and Yang, Yinfei},
title = {Text-to-Image Generation Grounded by Fine-Grained User Attention},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Localized Narratives is a dataset with detailed natural language descriptions of images paired with mouse traces that provide a sparse, fine-grained visual grounding for phrases. We propose TReCS, a sequential model that exploits this grounding to generate images. TReCS uses descriptions to retrieve segmentation masks ... |
Prasad_maskedFaceNet_A_Progressive_Semi-Supervised_Masked_Face_Detector_WACV_2021_paper | maskedFaceNet: A Progressive Semi-Supervised Masked Face Detector | [
"Shitala Prasad",
"Yiqun Li",
"Dongyun Lin",
"Dong Sheng"
] | https://openaccess.thecvf.com/content/WACV2021/html/Prasad_maskedFaceNet_A_Progressive_Semi-Supervised_Masked_Face_Detector_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Prasad_maskedFaceNet_A_Progressive_Semi-Supervised_Masked_Face_Detector_WACV_2021_paper.pdf | null | null | null | @InProceedings{Prasad_2021_WACV,
author = {Prasad, Shitala and Li, Yiqun and Lin, Dongyun and Sheng, Dong},
title = {maskedFaceNet: A Progressive Semi-Supervised Masked Face Detector},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | To reduce the risk of infecting or being infected by the recent COVID-19 virus, wearing mask is enforced or recommended by many countries. AI based system for automatically detecting whether individuals are wearing face mask becomes an urgent requirement in high risk facilities and crowded public places. Due to lacking... |
Zhang_Adaptive_Privacy_Preserving_Deep_Learning_Algorithms_for_Medical_Data_WACV_2021_paper | Adaptive Privacy Preserving Deep Learning Algorithms for Medical Data | [
"Xinyue Zhang",
"Jiahao Ding",
"Maoqiang Wu",
"Stephen T.C. Wong",
"Hien Van Nguyen",
"Miao Pan"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Adaptive_Privacy_Preserving_Deep_Learning_Algorithms_for_Medical_Data_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Adaptive_Privacy_Preserving_Deep_Learning_Algorithms_for_Medical_Data_WACV_2021_paper.pdf | null | null | null | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Xinyue and Ding, Jiahao and Wu, Maoqiang and Wong, Stephen T.C. and Van Nguyen, Hien and Pan, Miao},
title = {Adaptive Privacy Preserving Deep Learning Algorithms for Medical Data},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicat... | Deep learning holds a great promise of revolutionizing healthcare and medicine. Unfortunately, various inference attack models demonstrated that deep learning puts sensitive patient information at risk. The high capacity of deep neural networks is the main reason behind the privacy loss. In particular, patient informat... |
Khodadadeh_Automatic_Object_Recoloring_Using_Adversarial_Learning_WACV_2021_paper | Automatic Object Recoloring Using Adversarial Learning | [
"Siavash Khodadadeh",
"Saeid Motiian",
"Zhe Lin",
"Ladislau Boloni",
"Shabnam Ghadar"
] | https://openaccess.thecvf.com/content/WACV2021/html/Khodadadeh_Automatic_Object_Recoloring_Using_Adversarial_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Khodadadeh_Automatic_Object_Recoloring_Using_Adversarial_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Khodadadeh_Automatic_Object_Recoloring_WACV_2021_supplemental.pdf | null | null | @InProceedings{Khodadadeh_2021_WACV,
author = {Khodadadeh, Siavash and Motiian, Saeid and Lin, Zhe and Boloni, Ladislau and Ghadar, Shabnam},
title = {Automatic Object Recoloring Using Adversarial Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision... | We propose a novel method for automatic object recoloring based on Generative Adversarial Networks (GANs). The user can simply give commands of the form ""recolor <object> to <color>"" which will be executed without any need of manual edit. Our approach takes advantage of pre-trained object detectors and saliency mask ... |
Zuo_Improved_Training_of_Generative_Adversarial_Networks_Using_Decision_Forests_WACV_2021_paper | Improved Training of Generative Adversarial Networks Using Decision Forests | [
"Yan Zuo",
"Gil Avraham",
"Tom Drummond"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zuo_Improved_Training_of_Generative_Adversarial_Networks_Using_Decision_Forests_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zuo_Improved_Training_of_Generative_Adversarial_Networks_Using_Decision_Forests_WACV_2021_paper.pdf | null | null | null | @InProceedings{Zuo_2021_WACV,
author = {Zuo, Yan and Avraham, Gil and Drummond, Tom},
title = {Improved Training of Generative Adversarial Networks Using Decision Forests},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January}... | Whilst Generative Adversarial Networks (GANs) have gained a reputation as powerful generative models, they are notoriously difficult to train and suffer from instability in optimisation. Recent methods for tackling this drawback have typically approached it by inducing better behaviour on the discriminator component of... |
Saeedan_Boosting_Monocular_Depth_With_Panoptic_Segmentation_Maps_WACV_2021_paper | Boosting Monocular Depth With Panoptic Segmentation Maps | [
"Faraz Saeedan",
"Stefan Roth"
] | https://openaccess.thecvf.com/content/WACV2021/html/Saeedan_Boosting_Monocular_Depth_With_Panoptic_Segmentation_Maps_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Saeedan_Boosting_Monocular_Depth_With_Panoptic_Segmentation_Maps_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Saeedan_Boosting_Monocular_Depth_WACV_2021_supplemental.pdf | null | null | @InProceedings{Saeedan_2021_WACV,
author = {Saeedan, Faraz and Roth, Stefan},
title = {Boosting Monocular Depth With Panoptic Segmentation Maps},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
... | Monocular depth prediction is ill-posed by nature; hence successful approaches need to exploit the available cues to the fullest. Yet, real-world training data with depth ground-truth suffers from limited variability, and data acquired from depth sensors is also sparse and prone to noise. While available datasets with ... |
Yang_Context-Aware_Domain_Adaptation_in_Semantic_Segmentation_WACV_2021_paper | Context-Aware Domain Adaptation in Semantic Segmentation | [
"Jinyu Yang",
"Weizhi An",
"Chaochao Yan",
"Peilin Zhao",
"Junzhou Huang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yang_Context-Aware_Domain_Adaptation_in_Semantic_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yang_Context-Aware_Domain_Adaptation_in_Semantic_Segmentation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Yang_Context-Aware_Domain_Adaptation_WACV_2021_supplemental.pdf | 2003.04010 | cvf | @InProceedings{Yang_2021_WACV,
author = {Yang, Jinyu and An, Weizhi and Yan, Chaochao and Zhao, Peilin and Huang, Junzhou},
title = {Context-Aware Domain Adaptation in Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mo... | In this paper, we consider the problem of unsupervised domain adaptation in the semantic segmentation. There are two primary issues in this field, i.e., what and how to transfer domain knowledge across two domains. Existing methods mainly focus on adapting domain-invariant features (what to transfer) through adversaria... |
Seo_Neural_Contrast_Enhancement_of_CT_Image_WACV_2021_paper | Neural Contrast Enhancement of CT Image | [
"Minkyo Seo",
"Dongkeun Kim",
"Kyungmoon Lee",
"Seunghoon Hong",
"Jae Seok Bae",
"Jung Hoon Kim",
"Suha Kwak"
] | https://openaccess.thecvf.com/content/WACV2021/html/Seo_Neural_Contrast_Enhancement_of_CT_Image_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Seo_Neural_Contrast_Enhancement_of_CT_Image_WACV_2021_paper.pdf | null | null | null | @InProceedings{Seo_2021_WACV,
author = {Seo, Minkyo and Kim, Dongkeun and Lee, Kyungmoon and Hong, Seunghoon and Bae, Jae Seok and Kim, Jung Hoon and Kwak, Suha},
title = {Neural Contrast Enhancement of CT Image},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer ... | Contrast materials are often injected into body to contrast specific tissues in Computed Tomography (CT) images. Contrast Enhanced CT (CECT) images obtained in this way are more useful than Non-Enhanced CT (NECT) images for medical diagnosis, but not available for everyone due to side effects of the contrast materials.... |
Zhang_TB-Net_A_Three-Stream_Boundary-Aware_Network_for_Fine-Grained_Pavement_Disease_Segmentation_WACV_2021_paper | TB-Net: A Three-Stream Boundary-Aware Network for Fine-Grained Pavement Disease Segmentation | [
"Yujia Zhang",
"Qianzhong Li",
"Xiaoguang Zhao",
"Min Tan"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_TB-Net_A_Three-Stream_Boundary-Aware_Network_for_Fine-Grained_Pavement_Disease_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_TB-Net_A_Three-Stream_Boundary-Aware_Network_for_Fine-Grained_Pavement_Disease_Segmentation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Zhang_TB-Net_A_Three-Stream_WACV_2021_supplemental.pdf | 2011.03703 | title_snapshot | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Yujia and Li, Qianzhong and Zhao, Xiaoguang and Tan, Min},
title = {TB-Net: A Three-Stream Boundary-Aware Network for Fine-Grained Pavement Disease Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vi... | Regular pavement inspection plays a significant role in road maintenance for safety assurance. Existing methods mainly address the tasks of crack detection and segmentation that are only tailored for long-thin crack disease. However, there are many other types of diseases with a wider variety of sizes and patterns that... |
Ishikawa_Alleviating_Over-Segmentation_Errors_by_Detecting_Action_Boundaries_WACV_2021_paper | Alleviating Over-Segmentation Errors by Detecting Action Boundaries | [
"Yuchi Ishikawa",
"Seito Kasai",
"Yoshimitsu Aoki",
"Hirokatsu Kataoka"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ishikawa_Alleviating_Over-Segmentation_Errors_by_Detecting_Action_Boundaries_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ishikawa_Alleviating_Over-Segmentation_Errors_by_Detecting_Action_Boundaries_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Ishikawa_Alleviating_Over-Segmentation_Errors_WACV_2021_supplemental.zip | 2007.06866 | cvf | @InProceedings{Ishikawa_2021_WACV,
author = {Ishikawa, Yuchi and Kasai, Seito and Aoki, Yoshimitsu and Kataoka, Hirokatsu},
title = {Alleviating Over-Segmentation Errors by Detecting Action Boundaries},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WAC... | We propose an effective framework for the temporal action segmentation task, namely an Action Segment Refinement Framework (ASRF). Our model architecture consists of a long-term feature extractor and two branches: the Action Segmentation Branch (ASB) and the Boundary Regression Branch (BRB). The long-term feature extra... |
Yu_Towards_Resolving_the_Challenge_of_Long-Tail_Distribution_in_UAV_Images_WACV_2021_paper | Towards Resolving the Challenge of Long-Tail Distribution in UAV Images for Object Detection | [
"Weiping Yu",
"Taojiannan Yang",
"Chen Chen"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yu_Towards_Resolving_the_Challenge_of_Long-Tail_Distribution_in_UAV_Images_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yu_Towards_Resolving_the_Challenge_of_Long-Tail_Distribution_in_UAV_Images_WACV_2021_paper.pdf | null | 2011.03822 | cvf | @InProceedings{Yu_2021_WACV,
author = {Yu, Weiping and Yang, Taojiannan and Chen, Chen},
title = {Towards Resolving the Challenge of Long-Tail Distribution in UAV Images for Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
m... | Existing methods for object detection in UAV images ignored an important challenge -- imbalanced class distribution -- which leads to poor performance on tail classes. We systematically investigate existing solutions to long-tail problems and unveil that re-balancing methods that are effective on natural image datasets... |
Rakhimov_Making_DensePose_Fast_and_Light_WACV_2021_paper | Making DensePose Fast and Light | [
"Ruslan Rakhimov",
"Emil Bogomolov",
"Alexandr Notchenko",
"Fung Mao",
"Alexey Artemov",
"Denis Zorin",
"Evgeny Burnaev"
] | https://openaccess.thecvf.com/content/WACV2021/html/Rakhimov_Making_DensePose_Fast_and_Light_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Rakhimov_Making_DensePose_Fast_and_Light_WACV_2021_paper.pdf | null | 2006.15190 | cvf | @InProceedings{Rakhimov_2021_WACV,
author = {Rakhimov, Ruslan and Bogomolov, Emil and Notchenko, Alexandr and Mao, Fung and Artemov, Alexey and Zorin, Denis and Burnaev, Evgeny},
title = {Making DensePose Fast and Light},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of C... | DensePose estimation task is a significant step forward for enhancing user experience computer vision applications ranging from augmented reality to cloth fitting. Existing neural network models capable of solving this task are heavily parameterized and a long way from being transferred to an embedded or mobile device.... |
Chen_MVHM_A_Large-Scale_Multi-View_Hand_Mesh_Benchmark_for_Accurate_3D_WACV_2021_paper | MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation | [
"Liangjian Chen",
"Shih-Yao Lin",
"Yusheng Xie",
"Yen-Yu Lin",
"Xiaohui Xie"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chen_MVHM_A_Large-Scale_Multi-View_Hand_Mesh_Benchmark_for_Accurate_3D_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chen_MVHM_A_Large-Scale_Multi-View_Hand_Mesh_Benchmark_for_Accurate_3D_WACV_2021_paper.pdf | null | 2012.03206 | cvf | @InProceedings{Chen_2021_WACV,
author = {Chen, Liangjian and Lin, Shih-Yao and Xie, Yusheng and Lin, Yen-Yu and Xie, Xiaohui},
title = {MVHM: A Large-Scale Multi-View Hand Mesh Benchmark for Accurate 3D Hand Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications ... | Estimating 3D hand poses from a single RGB image is challenging because depth ambiguity leads the problem ill-posed. Training hand pose estimators with 3D hand mesh annotations and multi-view images often results in significant performance gains. However, existing multi-view datasets are relatively small with hand join... |
Moreira_Fast_Pose_Graph_Optimization_via_Krylov-Schur_and_Cholesky_Factorization_WACV_2021_paper | Fast Pose Graph Optimization via Krylov-Schur and Cholesky Factorization | [
"Gabriel Moreira",
"Manuel Marques",
"Joao Paulo Costeira"
] | https://openaccess.thecvf.com/content/WACV2021/html/Moreira_Fast_Pose_Graph_Optimization_via_Krylov-Schur_and_Cholesky_Factorization_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Moreira_Fast_Pose_Graph_Optimization_via_Krylov-Schur_and_Cholesky_Factorization_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Moreira_Fast_Pose_Graph_WACV_2021_supplemental.zip | null | null | @InProceedings{Moreira_2021_WACV,
author = {Moreira, Gabriel and Marques, Manuel and Costeira, Joao Paulo},
title = {Fast Pose Graph Optimization via Krylov-Schur and Cholesky Factorization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mo... | Pose Graph Optimization (PGO) is an important problem in Computer Vision, particularly in motion estimation, whose objective consists of finding the rigid transformations that achieve the best global alignment of visual data on a common reference frame. The vast majority of PGO approaches rely on iterative techniques w... |
Domnik_Dense_3D-Reconstruction_From_Monocular_Image_Sequences_for_Computationally_Constrained_UAS_WACV_2021_paper | Dense 3D-Reconstruction From Monocular Image Sequences for Computationally Constrained UAS | [
"Matthias Domnik",
"Pedro Proenca",
"Jeff Delaune",
"Jorg Thiem",
"Roland Brockers"
] | https://openaccess.thecvf.com/content/WACV2021/html/Domnik_Dense_3D-Reconstruction_From_Monocular_Image_Sequences_for_Computationally_Constrained_UAS_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Domnik_Dense_3D-Reconstruction_From_Monocular_Image_Sequences_for_Computationally_Constrained_UAS_WACV_2021_paper.pdf | null | null | null | @InProceedings{Domnik_2021_WACV,
author = {Domnik, Matthias and Proenca, Pedro and Delaune, Jeff and Thiem, Jorg and Brockers, Roland},
title = {Dense 3D-Reconstruction From Monocular Image Sequences for Computationally Constrained UAS},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on A... | The ability to find safe landing sites over complex 3D terrain is an essential safety feature for fully autonomous small unmanned aerial systems (UAS), which requires on-board perception for 3D reconstruction and terrain analysis if the overflown terrain is unknown. This is a challenge for UAS that are limited in size,... |
Rodriguez-Opazo_DORi_Discovering_Object_Relationships_for_Moment_Localization_of_a_Natural_WACV_2021_paper | DORi: Discovering Object Relationships for Moment Localization of a Natural Language Query in a Video | [
"Cristian Rodriguez-Opazo",
"Edison Marrese-Taylor",
"Basura Fernando",
"Hongdong Li",
"Stephen Gould"
] | https://openaccess.thecvf.com/content/WACV2021/html/Rodriguez-Opazo_DORi_Discovering_Object_Relationships_for_Moment_Localization_of_a_Natural_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Rodriguez-Opazo_DORi_Discovering_Object_Relationships_for_Moment_Localization_of_a_Natural_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Rodriguez-Opazo_DORi_Discovering_Object_WACV_2021_supplemental.pdf | 2010.06260 | title_judge | @InProceedings{Rodriguez-Opazo_2021_WACV,
author = {Rodriguez-Opazo, Cristian and Marrese-Taylor, Edison and Fernando, Basura and Li, Hongdong and Gould, Stephen},
title = {DORi: Discovering Object Relationships for Moment Localization of a Natural Language Query in a Video},
booktitle = {Proceedings... | This paper studies the task of temporal moment localization in a long untrimmed video using natural language query. Given a query sentence, the goal is to determine the start and end of the relevant segment within the video. Our key innovation is to learn a video feature embedding through a language-conditioned message... |
Olsson_ClassMix_Segmentation-Based_Data_Augmentation_for_Semi-Supervised_Learning_WACV_2021_paper | ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning | [
"Viktor Olsson",
"Wilhelm Tranheden",
"Juliano Pinto",
"Lennart Svensson"
] | https://openaccess.thecvf.com/content/WACV2021/html/Olsson_ClassMix_Segmentation-Based_Data_Augmentation_for_Semi-Supervised_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Olsson_ClassMix_Segmentation-Based_Data_Augmentation_for_Semi-Supervised_Learning_WACV_2021_paper.pdf | null | 2007.07936 | cvf | @InProceedings{Olsson_2021_WACV,
author = {Olsson, Viktor and Tranheden, Wilhelm and Pinto, Juliano and Svensson, Lennart},
title = {ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vis... | The state of the art in semantic segmentation is steadily increasing in performance, resulting in more precise and reliable segmentations in many different applications. However, progress is limited by the cost of generating labels for training, which sometimes requires hours of manual labor for a single image. Because... |
Zhang_Deep_Image_Compositing_WACV_2021_paper | Deep Image Compositing | [
"He Zhang",
"Jianming Zhang",
"Federico Perazzi",
"Zhe Lin",
"Vishal M. Patel"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Deep_Image_Compositing_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Deep_Image_Compositing_WACV_2021_paper.pdf | null | 2011.02146 | cvf | @InProceedings{Zhang_2021_WACV,
author = {Zhang, He and Zhang, Jianming and Perazzi, Federico and Lin, Zhe and Patel, Vishal M.},
title = {Deep Image Compositing},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
yea... | Image compositing is a task of combining regions from different images to compose a new image. A common use case is background replacement of portrait images. To obtain high quality composites, professionals typically manually perform multiple editing steps such as segmentation, matting and foreground color decontamina... |
Hou_Novel_View_Synthesis_via_Depth-Guided_Skip_Connections_WACV_2021_paper | Novel View Synthesis via Depth-Guided Skip Connections | [
"Yuxin Hou",
"Arno Solin",
"Juho Kannala"
] | https://openaccess.thecvf.com/content/WACV2021/html/Hou_Novel_View_Synthesis_via_Depth-Guided_Skip_Connections_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Hou_Novel_View_Synthesis_via_Depth-Guided_Skip_Connections_WACV_2021_paper.pdf | null | 2101.01619 | title_snapshot | @InProceedings{Hou_2021_WACV,
author = {Hou, Yuxin and Solin, Arno and Kannala, Juho},
title = {Novel View Synthesis via Depth-Guided Skip Connections},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2... | We introduce a principled approach for synthesizing new views of a scene given a single source image. Previous methods for novel view synthesis can be divided into image-based rendering methods (e.g, flow prediction) or pixel generation methods. Flow predictions enable the target view to re-use pixels directly, but can... |
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