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 37 123 | title stringlengths 14 147 | authors listlengths 1 17 | cvf_url stringlengths 94 180 | pdf_url stringlengths 95 181 | supp_url stringlengths 102 137 ⌀ | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 3
values | bibtex large_stringlengths 313 643 | abstract large_stringlengths 680 2k |
|---|---|---|---|---|---|---|---|---|---|
Agarwal_Does_Data_Repair_Lead_to_Fair_Models_Curating_Contextually_Fair_WACV_2022_paper | Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias | [
"Sharat Agarwal",
"Sumanyu Muku",
"Saket Anand",
"Chetan Arora"
] | https://openaccess.thecvf.com/content/WACV2022/html/Agarwal_Does_Data_Repair_Lead_to_Fair_Models_Curating_Contextually_Fair_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Agarwal_Does_Data_Repair_Lead_to_Fair_Models_Curating_Contextually_Fair_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Agarwal_Does_Data_Repair_WACV_2022_supplemental.pdf | 2110.10389 | cvf | @InProceedings{Agarwal_2022_WACV,
author = {Agarwal, Sharat and Muku, Sumanyu and Anand, Saket and Arora, Chetan},
title = {Does Data Repair Lead to Fair Models? Curating Contextually Fair Data To Reduce Model Bias},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comput... | Contextual information is a valuable cue for Deep Neural Networks (DNNs) to learn better representations and improve accuracy. However, co-occurrence bias in the training dataset may hamper a DNN model's generalizability to unseen scenarios in the real world. For example, in COCO [??], many object categories have a muc... |
Hatamizadeh_UNETR_Transformers_for_3D_Medical_Image_Segmentation_WACV_2022_paper | UNETR: Transformers for 3D Medical Image Segmentation | [
"Ali Hatamizadeh",
"Yucheng Tang",
"Vishwesh Nath",
"Dong Yang",
"Andriy Myronenko",
"Bennett Landman",
"Holger R. Roth",
"Daguang Xu"
] | https://openaccess.thecvf.com/content/WACV2022/html/Hatamizadeh_UNETR_Transformers_for_3D_Medical_Image_Segmentation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Hatamizadeh_UNETR_Transformers_for_3D_Medical_Image_Segmentation_WACV_2022_paper.pdf | null | 2103.10504 | cvf | @InProceedings{Hatamizadeh_2022_WACV,
author = {Hatamizadeh, Ali and Tang, Yucheng and Nath, Vishwesh and Yang, Dong and Myronenko, Andriy and Landman, Bennett and Roth, Holger R. and Xu, Daguang},
title = {UNETR: Transformers for 3D Medical Image Segmentation},
booktitle = {Proceedings of the IEEE/C... | Fully Convolutional Neural Networks (FCNNs) with contracting and expanding paths have shown prominence for the majority of medical image segmentation applications since the past decade. In FCNNs, the encoder plays an integral role by learning both global and local features and contextual representations which can be ut... |
Peng_SIDE_Center-Based_Stereo_3D_Detector_With_Structure-Aware_Instance_Depth_Estimation_WACV_2022_paper | SIDE: Center-Based Stereo 3D Detector With Structure-Aware Instance Depth Estimation | [
"Xidong Peng",
"Xinge Zhu",
"Tai Wang",
"Yuexin Ma"
] | https://openaccess.thecvf.com/content/WACV2022/html/Peng_SIDE_Center-Based_Stereo_3D_Detector_With_Structure-Aware_Instance_Depth_Estimation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Peng_SIDE_Center-Based_Stereo_3D_Detector_With_Structure-Aware_Instance_Depth_Estimation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Peng_SIDE_Center-Based_Stereo_WACV_2022_supplemental.pdf | 2108.09663 | cvf | @InProceedings{Peng_2022_WACV,
author = {Peng, Xidong and Zhu, Xinge and Wang, Tai and Ma, Yuexin},
title = {SIDE: Center-Based Stereo 3D Detector With Structure-Aware Instance Depth Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | 3D detection plays an indispensable role in environment perception. Due to the high cost of commonly used LiDAR sensor, stereo vision based 3D detection, as an economical yet effective setting, attracts more attention recently. For these approaches based on 2D images, accurate depth information is the key to achieve 3D... |
Bhaskara_GraN-GAN_Piecewise_Gradient_Normalization_for_Generative_Adversarial_Networks_WACV_2022_paper | GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks | [
"Vineeth S. Bhaskara",
"Tristan Aumentado-Armstrong",
"Allan D. Jepson",
"Alex Levinshtein"
] | https://openaccess.thecvf.com/content/WACV2022/html/Bhaskara_GraN-GAN_Piecewise_Gradient_Normalization_for_Generative_Adversarial_Networks_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Bhaskara_GraN-GAN_Piecewise_Gradient_Normalization_for_Generative_Adversarial_Networks_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Bhaskara_GraN-GAN_Piecewise_Gradient_WACV_2022_supplemental.pdf | 2111.03162 | title_snapshot | @InProceedings{Bhaskara_2022_WACV,
author = {Bhaskara, Vineeth S. and Aumentado-Armstrong, Tristan and Jepson, Allan D. and Levinshtein, Alex},
title = {GraN-GAN: Piecewise Gradient Normalization for Generative Adversarial Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Appli... | Modern generative adversarial networks (GANs) predominantly use piecewise linear activation functions in discriminators (or critics), including ReLU and LeakyReLU. Such models learn piecewise linear mappings, where each piece handles a subset of the input space, and the gradients per subset are piecewise constant. Unde... |
VS_Meta-UDA_Unsupervised_Domain_Adaptive_Thermal_Object_Detection_Using_Meta-Learning_WACV_2022_paper | Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection Using Meta-Learning | [
"Vibashan VS",
"Domenick Poster",
"Suya You",
"Shuowen Hu",
"Vishal M. Patel"
] | https://openaccess.thecvf.com/content/WACV2022/html/VS_Meta-UDA_Unsupervised_Domain_Adaptive_Thermal_Object_Detection_Using_Meta-Learning_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/VS_Meta-UDA_Unsupervised_Domain_Adaptive_Thermal_Object_Detection_Using_Meta-Learning_WACV_2022_paper.pdf | null | 2110.03143 | title_snapshot | @InProceedings{VS_2022_WACV,
author = {VS, Vibashan and Poster, Domenick and You, Suya and Hu, Shuowen and Patel, Vishal M.},
title = {Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection Using Meta-Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Co... | Object detectors trained on large-scale RGB datasets are being extensively employed in real-world applications. However, these RGB-trained models suffer a performance drop under adverse illumination and lighting conditions. Infrared (IR) cameras are robust under such conditions and can be helpful in real-world applicat... |
Chen_Multi-Level_Attentive_Adversarial_Learning_With_Temporal_Dilation_for_Unsupervised_Video_WACV_2022_paper | Multi-Level Attentive Adversarial Learning With Temporal Dilation for Unsupervised Video Domain Adaptation | [
"Peipeng Chen",
"Yuan Gao",
"Andy J. Ma"
] | https://openaccess.thecvf.com/content/WACV2022/html/Chen_Multi-Level_Attentive_Adversarial_Learning_With_Temporal_Dilation_for_Unsupervised_Video_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Chen_Multi-Level_Attentive_Adversarial_Learning_With_Temporal_Dilation_for_Unsupervised_Video_WACV_2022_paper.pdf | null | null | null | @InProceedings{Chen_2022_WACV,
author = {Chen, Peipeng and Gao, Yuan and Ma, Andy J.},
title = {Multi-Level Attentive Adversarial Learning With Temporal Dilation for Unsupervised Video Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | Most existing works on unsupervised video domain adaptation attempt to mitigate the distribution gap across domains in frame and video levels. Such two-level distribution alignment approach may suffer from the problems of insufficient alignment for complex video data and misalignment along the temporal dimension. To ad... |
Degardin_Generative_Adversarial_Graph_Convolutional_Networks_for_Human_Action_Synthesis_WACV_2022_paper | Generative Adversarial Graph Convolutional Networks for Human Action Synthesis | [
"Bruno Degardin",
"João Neves",
"Vasco Lopes",
"João Brito",
"Ehsan Yaghoubi",
"Hugo Proença"
] | https://openaccess.thecvf.com/content/WACV2022/html/Degardin_Generative_Adversarial_Graph_Convolutional_Networks_for_Human_Action_Synthesis_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Degardin_Generative_Adversarial_Graph_Convolutional_Networks_for_Human_Action_Synthesis_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Degardin_Generative_Adversarial_Graph_WACV_2022_supplemental.pdf | 2110.11191 | cvf | @InProceedings{Degardin_2022_WACV,
author = {Degardin, Bruno and Neves, Jo\~ao and Lopes, Vasco and Brito, Jo\~ao and Yaghoubi, Ehsan and Proen\c{c}a, Hugo},
title = {Generative Adversarial Graph Convolutional Networks for Human Action Synthesis},
booktitle = {Proceedings of the IEEE/CVF Winter Confe... | Synthesising the spatial and temporal dynamics of the human body skeleton remains a challenging task, not only in terms of the quality of the generated shapes, but also of their diversity, particularly to synthesise realistic body movements of a specific action (action conditioning). In this paper, we propose Kinetic-G... |
Guan_Non-Blind_Deblurring_for_Fluorescence_A_Deformable_Latent_Space_Approach_With_WACV_2022_paper | Non-Blind Deblurring for Fluorescence: A Deformable Latent Space Approach With Kernel Parameterization | [
"Ziqiao Guan",
"Esther H. R. Tsai",
"Xiaojing Huang",
"Kevin G. Yager",
"Hong Qin"
] | https://openaccess.thecvf.com/content/WACV2022/html/Guan_Non-Blind_Deblurring_for_Fluorescence_A_Deformable_Latent_Space_Approach_With_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Guan_Non-Blind_Deblurring_for_Fluorescence_A_Deformable_Latent_Space_Approach_With_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Guan_Non-Blind_Deblurring_for_WACV_2022_supplemental.pdf | null | null | @InProceedings{Guan_2022_WACV,
author = {Guan, Ziqiao and Tsai, Esther H. R. and Huang, Xiaojing and Yager, Kevin G. and Qin, Hong},
title = {Non-Blind Deblurring for Fluorescence: A Deformable Latent Space Approach With Kernel Parameterization},
booktitle = {Proceedings of the IEEE/CVF Winter Confer... | Non-blind deblurring (NBD) is a modeling method of the image deblurring problem in computer vision, where the blurring kernel is known or can be externally estimated. In this paper, we attempt to solve a parametric NBD problem, inspired by the simultaneous acquisition of ptychography and fluorescent imaging (FI). Ptych... |
Pal_Few-Shot_Open-Set_Recognition_of_Hyperspectral_Images_With_Outlier_Calibration_Network_WACV_2022_paper | Few-Shot Open-Set Recognition of Hyperspectral Images With Outlier Calibration Network | [
"Debabrata Pal",
"Valay Bundele",
"Renuka Sharma",
"Biplab Banerjee",
"Yogananda Jeppu"
] | https://openaccess.thecvf.com/content/WACV2022/html/Pal_Few-Shot_Open-Set_Recognition_of_Hyperspectral_Images_With_Outlier_Calibration_Network_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Pal_Few-Shot_Open-Set_Recognition_of_Hyperspectral_Images_With_Outlier_Calibration_Network_WACV_2022_paper.pdf | null | null | null | @InProceedings{Pal_2022_WACV,
author = {Pal, Debabrata and Bundele, Valay and Sharma, Renuka and Banerjee, Biplab and Jeppu, Yogananda},
title = {Few-Shot Open-Set Recognition of Hyperspectral Images With Outlier Calibration Network},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Appl... | We tackle the few-shot open-set recognition (FSOSR) problem in the context of remote sensing hyperspectral image (HSI) classification. Prior research on OSR mainly considers an empirical threshold on the class prediction scores to reject the outlier samples. Further, recent endeavors in few-shot HSI classification fail... |
Gupta_SBEVNet_End-to-End_Deep_Stereo_Layout_Estimation_WACV_2022_paper | SBEVNet: End-to-End Deep Stereo Layout Estimation | [
"Divam Gupta",
"Wei Pu",
"Trenton Tabor",
"Jeff Schneider"
] | https://openaccess.thecvf.com/content/WACV2022/html/Gupta_SBEVNet_End-to-End_Deep_Stereo_Layout_Estimation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Gupta_SBEVNet_End-to-End_Deep_Stereo_Layout_Estimation_WACV_2022_paper.pdf | null | 2105.11705 | cvf | @InProceedings{Gupta_2022_WACV,
author = {Gupta, Divam and Pu, Wei and Tabor, Trenton and Schneider, Jeff},
title = {SBEVNet: End-to-End Deep Stereo Layout Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | Accurate layout estimation is crucial for planning and navigation in robotics applications, such as self-driving. In this paper, we introduce the Stereo Bird's Eye ViewNetwork (SBEVNet), a novel supervised end-to-end framework for estimation of bird's eye view layout from a pair of stereo images. Although our network r... |
Belharbi_F-CAM_Full_Resolution_Class_Activation_Maps_via_Guided_Parametric_Upscaling_WACV_2022_paper | F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling | [
"Soufiane Belharbi",
"Aydin Sarraf",
"Marco Pedersoli",
"Ismail Ben Ayed",
"Luke McCaffrey",
"Eric Granger"
] | https://openaccess.thecvf.com/content/WACV2022/html/Belharbi_F-CAM_Full_Resolution_Class_Activation_Maps_via_Guided_Parametric_Upscaling_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Belharbi_F-CAM_Full_Resolution_Class_Activation_Maps_via_Guided_Parametric_Upscaling_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Belharbi_F-CAM_Full_Resolution_WACV_2022_supplemental.pdf | 2109.07069 | title_snapshot | @InProceedings{Belharbi_2022_WACV,
author = {Belharbi, Soufiane and Sarraf, Aydin and Pedersoli, Marco and Ben Ayed, Ismail and McCaffrey, Luke and Granger, Eric},
title = {F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling},
booktitle = {Proceedings of the IEEE/CVF Winter C... | Class Activation Mapping (CAM) methods have recently gained much attention for weakly-supervised object localization (WSOL) tasks. They allow for CNN visualization and interpretation without training on fully annotated image datasets. CAM methods are typically integrated within off-the-shelf CNN backbones, such as ResN... |
Birhane_Auditing_Saliency_Cropping_Algorithms_WACV_2022_paper | Auditing Saliency Cropping Algorithms | [
"Abeba Birhane",
"Vinay Uday Prabhu",
"John Whaley"
] | https://openaccess.thecvf.com/content/WACV2022/html/Birhane_Auditing_Saliency_Cropping_Algorithms_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Birhane_Auditing_Saliency_Cropping_Algorithms_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Birhane_Auditing_Saliency_Cropping_WACV_2022_supplemental.pdf | null | null | @InProceedings{Birhane_2022_WACV,
author = {Birhane, Abeba and Prabhu, Vinay Uday and Whaley, John},
title = {Auditing Saliency Cropping Algorithms},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022... | In this paper, we audit saliency cropping algorithms used by Twitter, Google and Apple to investigate issues pertaining to the male-gaze cropping phenomenon as well as race-gender biases that emerge in post-cropping survival ratios of face-images constituting 3 x 1 grid images. In doing so, we present the first formal ... |
Inkawhich_The_Untapped_Potential_of_Off-the-Shelf_Convolutional_Neural_Networks_WACV_2022_paper | The Untapped Potential of Off-the-Shelf Convolutional Neural Networks | [
"Matthew Inkawhich",
"Nathan Inkawhich",
"Eric Davis",
"Hai Li",
"Yiran Chen"
] | https://openaccess.thecvf.com/content/WACV2022/html/Inkawhich_The_Untapped_Potential_of_Off-the-Shelf_Convolutional_Neural_Networks_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Inkawhich_The_Untapped_Potential_of_Off-the-Shelf_Convolutional_Neural_Networks_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Inkawhich_The_Untapped_Potential_WACV_2022_supplemental.pdf | 2103.09891 | cvf | @InProceedings{Inkawhich_2022_WACV,
author = {Inkawhich, Matthew and Inkawhich, Nathan and Davis, Eric and Li, Hai and Chen, Yiran},
title = {The Untapped Potential of Off-the-Shelf Convolutional Neural Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer ... | Over recent years, a myriad of novel convolutional network architectures have been developed to advance state-of-the-art performance on challenging recognition tasks. As computational resources improve, a great deal of effort has been placed on efficiently scaling up existing designs and generating new architectures wi... |
Hu_X-MIR_EXplainable_Medical_Image_Retrieval_WACV_2022_paper | X-MIR: EXplainable Medical Image Retrieval | [
"Brian Hu",
"Bhavan Vasu",
"Anthony Hoogs"
] | https://openaccess.thecvf.com/content/WACV2022/html/Hu_X-MIR_EXplainable_Medical_Image_Retrieval_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Hu_X-MIR_EXplainable_Medical_Image_Retrieval_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Hu_X-MIR_EXplainable_Medical_WACV_2022_supplemental.pdf | null | null | @InProceedings{Hu_2022_WACV,
author = {Hu, Brian and Vasu, Bhavan and Hoogs, Anthony},
title = {X-MIR: EXplainable Medical Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pa... | Despite significant progress in the past few years, machine learning systems are still often viewed as "black boxes", which lack the ability to explain their output decisions. In high-stakes situations such as healthcare, there is a need for explainable AI (XAI) tools that can help open up this black box. In contrast t... |
Byun_On_the_Effectiveness_of_Small_Input_Noise_for_Defending_Against_WACV_2022_paper | On the Effectiveness of Small Input Noise for Defending Against Query-Based Black-Box Attacks | [
"Junyoung Byun",
"Hyojun Go",
"Changick Kim"
] | https://openaccess.thecvf.com/content/WACV2022/html/Byun_On_the_Effectiveness_of_Small_Input_Noise_for_Defending_Against_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Byun_On_the_Effectiveness_of_Small_Input_Noise_for_Defending_Against_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Byun_On_the_Effectiveness_WACV_2022_supplemental.pdf | 2101.04829 | cvf | @InProceedings{Byun_2022_WACV,
author = {Byun, Junyoung and Go, Hyojun and Kim, Changick},
title = {On the Effectiveness of Small Input Noise for Defending Against Query-Based Black-Box Attacks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | While deep neural networks show unprecedented performance in various tasks, the vulnerability to adversarial examples hinders their deployment in safety-critical systems. Many studies have shown that attacks are also possible even in a black-box setting where an adversary cannot access the target model's internal infor... |
Tan_A_Fast_Partial_Video_Copy_Detection_Using_KNN_and_Global_WACV_2022_paper | A Fast Partial Video Copy Detection Using KNN and Global Feature Database | [
"Weijun Tan",
"Hongwei Guo",
"Rushuai Liu"
] | https://openaccess.thecvf.com/content/WACV2022/html/Tan_A_Fast_Partial_Video_Copy_Detection_Using_KNN_and_Global_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Tan_A_Fast_Partial_Video_Copy_Detection_Using_KNN_and_Global_WACV_2022_paper.pdf | null | 2105.01713 | cvf | @InProceedings{Tan_2022_WACV,
author = {Tan, Weijun and Guo, Hongwei and Liu, Rushuai},
title = {A Fast Partial Video Copy Detection Using KNN and Global Feature Database},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January}... | Unlike in most previous partial video copy detection (PVCD) algorithms, where reference videos are scanned one by one, we treat the PVCD as a video search/retrieval problem. We propose a fast partial video copy detection framework in this paper. In this framework, all frame CNN features of the reference videos are orga... |
Sun_Information_Bottlenecked_Variational_Autoencoder_for_Disentangled_3D_Facial_Expression_Modelling_WACV_2022_paper | Information Bottlenecked Variational Autoencoder for Disentangled 3D Facial Expression Modelling | [
"Hao Sun",
"Nick Pears",
"Yajie Gu"
] | https://openaccess.thecvf.com/content/WACV2022/html/Sun_Information_Bottlenecked_Variational_Autoencoder_for_Disentangled_3D_Facial_Expression_Modelling_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Sun_Information_Bottlenecked_Variational_Autoencoder_for_Disentangled_3D_Facial_Expression_Modelling_WACV_2022_paper.pdf | null | null | null | @InProceedings{Sun_2022_WACV,
author = {Sun, Hao and Pears, Nick and Gu, Yajie},
title = {Information Bottlenecked Variational Autoencoder for Disentangled 3D Facial Expression Modelling},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | Learning a disentangled representation is essential to build 3D face models that accurately capture identity and expression. We propose a novel variational autoencoder (VAE) framework to disentangle identity and expression from 3D input faces that have a wide variety of expressions. Specifically, we design a system tha... |
Szymanowicz_Discrete_Neural_Representations_for_Explainable_Anomaly_Detection_WACV_2022_paper | Discrete Neural Representations for Explainable Anomaly Detection | [
"Stanislaw Szymanowicz",
"James Charles",
"Roberto Cipolla"
] | https://openaccess.thecvf.com/content/WACV2022/html/Szymanowicz_Discrete_Neural_Representations_for_Explainable_Anomaly_Detection_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Szymanowicz_Discrete_Neural_Representations_for_Explainable_Anomaly_Detection_WACV_2022_paper.pdf | null | 2112.05585 | cvf | @InProceedings{Szymanowicz_2022_WACV,
author = {Szymanowicz, Stanislaw and Charles, James and Cipolla, Roberto},
title = {Discrete Neural Representations for Explainable Anomaly Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mont... | The aim of this work is to detect and automatically generate high-level explanations of anomalous events in video. Understanding the cause of an anomalous event is crucial as the required response is dependant on its nature and severity. Recent works typically use object or action classifier to detect and provide label... |
Drenkow_Attack_Agnostic_Detection_of_Adversarial_Examples_via_Random_Subspace_Analysis_WACV_2022_paper | Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis | [
"Nathan Drenkow",
"Neil Fendley",
"Philippe Burlina"
] | https://openaccess.thecvf.com/content/WACV2022/html/Drenkow_Attack_Agnostic_Detection_of_Adversarial_Examples_via_Random_Subspace_Analysis_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Drenkow_Attack_Agnostic_Detection_of_Adversarial_Examples_via_Random_Subspace_Analysis_WACV_2022_paper.pdf | null | 2012.06405 | cvf | @InProceedings{Drenkow_2022_WACV,
author = {Drenkow, Nathan and Fendley, Neil and Burlina, Philippe},
title = {Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mo... | Whilst adversarial attack detection has received considerable attention, it remains a fundamentally challenging problem from two perspectives. First, while threat models can be well-defined, attacker strategies may still vary widely within those constraints. Therefore, detection should be considered as an open-set prob... |
Bucci_Distance-Based_Hyperspherical_Classification_for_Multi-Source_Open-Set_Domain_Adaptation_WACV_2022_paper | Distance-Based Hyperspherical Classification for Multi-Source Open-Set Domain Adaptation | [
"Silvia Bucci",
"Francesco Cappio Borlino",
"Barbara Caputo",
"Tatiana Tommasi"
] | https://openaccess.thecvf.com/content/WACV2022/html/Bucci_Distance-Based_Hyperspherical_Classification_for_Multi-Source_Open-Set_Domain_Adaptation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Bucci_Distance-Based_Hyperspherical_Classification_for_Multi-Source_Open-Set_Domain_Adaptation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Bucci_Distance-Based_Hyperspherical_Classification_WACV_2022_supplemental.pdf | 2107.02067 | cvf | @InProceedings{Bucci_2022_WACV,
author = {Bucci, Silvia and Borlino, Francesco Cappio and Caputo, Barbara and Tommasi, Tatiana},
title = {Distance-Based Hyperspherical Classification for Multi-Source Open-Set Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicatio... | Vision systems trained in closed-world scenarios fail when presented with new environmental conditions, new data distributions, and novel classes at deployment time. How to move towards open-world learning is a long-standing research question. The existing solutions mainly focus on specific aspects of the problem (sing... |
Schmidt_D2Conv3D_Dynamic_Dilated_Convolutions_for_Object_Segmentation_in_Videos_WACV_2022_paper | D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos | [
"Christian Schmidt",
"Ali Athar",
"Sabarinath Mahadevan",
"Bastian Leibe"
] | https://openaccess.thecvf.com/content/WACV2022/html/Schmidt_D2Conv3D_Dynamic_Dilated_Convolutions_for_Object_Segmentation_in_Videos_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Schmidt_D2Conv3D_Dynamic_Dilated_Convolutions_for_Object_Segmentation_in_Videos_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Schmidt_D2Conv3D_Dynamic_Dilated_WACV_2022_supplemental.pdf | 2111.07774 | title_judge | @InProceedings{Schmidt_2022_WACV,
author = {Schmidt, Christian and Athar, Ali and Mahadevan, Sabarinath and Leibe, Bastian},
title = {D2Conv3D: Dynamic Dilated Convolutions for Object Segmentation in Videos},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Visio... | Despite receiving significant attention from the research community, the task of segmenting and tracking objects in monocular videos still has much room for improvement. Existing works have simultaneously justified the efficacy of dilated and deformable convolutions for various image-level segmentation tasks. This give... |
Yang_Multi-Motion_and_Appearance_Self-Supervised_Moving_Object_Detection_WACV_2022_paper | Multi-Motion and Appearance Self-Supervised Moving Object Detection | [
"Fan Yang",
"Srikrishna Karanam",
"Meng Zheng",
"Terrence Chen",
"Haibin Ling",
"Ziyan Wu"
] | https://openaccess.thecvf.com/content/WACV2022/html/Yang_Multi-Motion_and_Appearance_Self-Supervised_Moving_Object_Detection_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Yang_Multi-Motion_and_Appearance_Self-Supervised_Moving_Object_Detection_WACV_2022_paper.pdf | null | null | null | @InProceedings{Yang_2022_WACV,
author = {Yang, Fan and Karanam, Srikrishna and Zheng, Meng and Chen, Terrence and Ling, Haibin and Wu, Ziyan},
title = {Multi-Motion and Appearance Self-Supervised Moving Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of C... | In this work, we consider the problem of self-supervised Moving Object Detection (MOD) in video, where no ground truth is involved in both training and inference phases. Recently, an adversarial learning framework is proposed to leverage inherent temporal information for MOD. While showing great promising results, it u... |
Jayasinghe_CeyMo_See_More_on_Roads_-_A_Novel_Benchmark_Dataset_WACV_2022_paper | CeyMo: See More on Roads - A Novel Benchmark Dataset for Road Marking Detection | [
"Oshada Jayasinghe",
"Sahan Hemachandra",
"Damith Anhettigama",
"Shenali Kariyawasam",
"Ranga Rodrigo",
"Peshala Jayasekara"
] | https://openaccess.thecvf.com/content/WACV2022/html/Jayasinghe_CeyMo_See_More_on_Roads_-_A_Novel_Benchmark_Dataset_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Jayasinghe_CeyMo_See_More_on_Roads_-_A_Novel_Benchmark_Dataset_WACV_2022_paper.pdf | null | 2110.11867 | title_snapshot | @InProceedings{Jayasinghe_2022_WACV,
author = {Jayasinghe, Oshada and Hemachandra, Sahan and Anhettigama, Damith and Kariyawasam, Shenali and Rodrigo, Ranga and Jayasekara, Peshala},
title = {CeyMo: See More on Roads - A Novel Benchmark Dataset for Road Marking Detection},
booktitle = {Proceedings of... | In this paper, we introduce a novel road marking benchmark dataset for road marking detection, addressing the limitations in the existing publicly available datasets such as lack of challenging scenarios, prominence given to lane markings, unavailability of an evaluation script, lack of annotation formats and lower res... |
Cho_Pixel-Level_Bijective_Matching_for_Video_Object_Segmentation_WACV_2022_paper | Pixel-Level Bijective Matching for Video Object Segmentation | [
"Suhwan Cho",
"Heansung Lee",
"Minjung Kim",
"Sungjun Jang",
"Sangyoun Lee"
] | https://openaccess.thecvf.com/content/WACV2022/html/Cho_Pixel-Level_Bijective_Matching_for_Video_Object_Segmentation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Cho_Pixel-Level_Bijective_Matching_for_Video_Object_Segmentation_WACV_2022_paper.pdf | null | 2110.01644 | cvf | @InProceedings{Cho_2022_WACV,
author = {Cho, Suhwan and Lee, Heansung and Kim, Minjung and Jang, Sungjun and Lee, Sangyoun},
title = {Pixel-Level Bijective Matching for Video Object Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Semi-supervised video object segmentation (VOS) aims to track a designated object present in the initial frame of a video at the pixel level. To fully exploit the appearance information of an object, pixel-level feature matching is widely used in VOS. Conventional feature matching runs in a surjective manner, i.e., onl... |
Nguyen_Unveiling_Real-Life_Effects_of_Online_Photo_Sharing_WACV_2022_paper | Unveiling Real-Life Effects of Online Photo Sharing | [
"Van-Khoa Nguyen",
"Adrian Popescu",
"Jérôme Deshayes-Chossart"
] | https://openaccess.thecvf.com/content/WACV2022/html/Nguyen_Unveiling_Real-Life_Effects_of_Online_Photo_Sharing_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Nguyen_Unveiling_Real-Life_Effects_of_Online_Photo_Sharing_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Nguyen_Unveiling_Real-Life_Effects_WACV_2022_supplemental.pdf | 2012.13180 | title_snapshot | @InProceedings{Nguyen_2022_WACV,
author = {Nguyen, Van-Khoa and Popescu, Adrian and Deshayes-Chossart, J\'er\^ome},
title = {Unveiling Real-Life Effects of Online Photo Sharing},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Ja... | Social networks give free access to their services in exchange for the right to exploit their users' data. Data sharing is done in an initial context which is chosen by the users. However, data are used by social networks and third parties in different contexts which are often not transparent. In order to unveil such u... |
Garg_HierMatch_Leveraging_Label_Hierarchies_for_Improving_Semi-Supervised_Learning_WACV_2022_paper | HierMatch: Leveraging Label Hierarchies for Improving Semi-Supervised Learning | [
"Ashima Garg",
"Shaurya Bagga",
"Yashvardhan Singh",
"Saket Anand"
] | https://openaccess.thecvf.com/content/WACV2022/html/Garg_HierMatch_Leveraging_Label_Hierarchies_for_Improving_Semi-Supervised_Learning_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Garg_HierMatch_Leveraging_Label_Hierarchies_for_Improving_Semi-Supervised_Learning_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Garg_HierMatch_Leveraging_Label_WACV_2022_supplemental.pdf | 2111.00164 | cvf | @InProceedings{Garg_2022_WACV,
author = {Garg, Ashima and Bagga, Shaurya and Singh, Yashvardhan and Anand, Saket},
title = {HierMatch: Leveraging Label Hierarchies for Improving Semi-Supervised Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | Semi-supervised learning approaches have emerged as an active area of research to combat the challenge of obtaining large amounts of annotated data. Towards the goal of improving the performance of semi-supervised learning methods, we propose a novel framework, HIERMATCH, a semi-supervised approach that leverages hiera... |
Bharadwaj_Mobile_Based_Human_Identification_Using_Forehead_Creases_Application_and_Assessment_WACV_2022_paper | Mobile Based Human Identification Using Forehead Creases: Application and Assessment Under COVID-19 Masked Face Scenarios | [
"Rohit Bharadwaj",
"Gaurav Jaswal",
"Aditya Nigam",
"Kamlesh Tiwari"
] | https://openaccess.thecvf.com/content/WACV2022/html/Bharadwaj_Mobile_Based_Human_Identification_Using_Forehead_Creases_Application_and_Assessment_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Bharadwaj_Mobile_Based_Human_Identification_Using_Forehead_Creases_Application_and_Assessment_WACV_2022_paper.pdf | null | null | null | @InProceedings{Bharadwaj_2022_WACV,
author = {Bharadwaj, Rohit and Jaswal, Gaurav and Nigam, Aditya and Tiwari, Kamlesh},
title = {Mobile Based Human Identification Using Forehead Creases: Application and Assessment Under COVID-19 Masked Face Scenarios},
booktitle = {Proceedings of the IEEE/CVF Winte... | In the COVID-19 situation, face masks have become an essential part of our daily life. As mask occludes most prominent facial characteristics, it brings new challenges to the existing facial recognition systems. This paper presents an idea to consider forehead creases (under surprise facial expression) as a new biometr... |
Parida_Beyond_Mono_to_Binaural_Generating_Binaural_Audio_From_Mono_Audio_WACV_2022_paper | Beyond Mono to Binaural: Generating Binaural Audio From Mono Audio With Depth and Cross Modal Attention | [
"Kranti Kumar Parida",
"Siddharth Srivastava",
"Gaurav Sharma"
] | https://openaccess.thecvf.com/content/WACV2022/html/Parida_Beyond_Mono_to_Binaural_Generating_Binaural_Audio_From_Mono_Audio_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Parida_Beyond_Mono_to_Binaural_Generating_Binaural_Audio_From_Mono_Audio_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Parida_Beyond_Mono_to_WACV_2022_supplemental.pdf | 2111.08046 | cvf | @InProceedings{Parida_2022_WACV,
author = {Parida, Kranti Kumar and Srivastava, Siddharth and Sharma, Gaurav},
title = {Beyond Mono to Binaural: Generating Binaural Audio From Mono Audio With Depth and Cross Modal Attention},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications ... | Binaural audio gives the listener an immersive experience and can enhance augmented and virtual reality. However, recording binaural audio requires specialized setup with a dummy human head having microphones in left and right ears. Such a recording setup is difficult to build and setup, therefore mono audio has become... |
Perez-Yus_Matching_and_Recovering_3D_People_From_Multiple_Views_WACV_2022_paper | Matching and Recovering 3D People From Multiple Views | [
"Alejandro Perez-Yus",
"Antonio Agudo"
] | https://openaccess.thecvf.com/content/WACV2022/html/Perez-Yus_Matching_and_Recovering_3D_People_From_Multiple_Views_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Perez-Yus_Matching_and_Recovering_3D_People_From_Multiple_Views_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Perez-Yus_Matching_and_Recovering_WACV_2022_supplemental.zip | null | null | @InProceedings{Perez-Yus_2022_WACV,
author = {Perez-Yus, Alejandro and Agudo, Antonio},
title = {Matching and Recovering 3D People From Multiple Views},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2... | This paper introduces an approach to simultaneously match and recover 3D people from multiple calibrated cameras. To this end, we present an affinity measure between 2D detections across different views that enforces an uncertainty geometric consistency. This similarity is then exploited by a novel multi-view matching ... |
Doshi_Rethinking_Video_Anomaly_Detection_-_A_Continual_Learning_Approach_WACV_2022_paper | Rethinking Video Anomaly Detection - A Continual Learning Approach | [
"Keval Doshi",
"Yasin Yilmaz"
] | https://openaccess.thecvf.com/content/WACV2022/html/Doshi_Rethinking_Video_Anomaly_Detection_-_A_Continual_Learning_Approach_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Doshi_Rethinking_Video_Anomaly_Detection_-_A_Continual_Learning_Approach_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Doshi_Rethinking_Video_Anomaly_WACV_2022_supplemental.pdf | null | null | @InProceedings{Doshi_2022_WACV,
author = {Doshi, Keval and Yilmaz, Yasin},
title = {Rethinking Video Anomaly Detection - A Continual Learning Approach},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2... | While video anomaly detection has been an active area of research for several years, recent progress is limited to improving the state-of-the-art results on small datasets using an inadequate evaluation criterion. In this work, we take a new comprehensive look at the video anomaly detection problem from a more realisti... |
Lee_A_Pixel-Level_Meta-Learner_for_Weakly_Supervised_Few-Shot_Semantic_Segmentation_WACV_2022_paper | A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation | [
"Yuan-Hao Lee",
"Fu-En Yang",
"Yu-Chiang Frank Wang"
] | https://openaccess.thecvf.com/content/WACV2022/html/Lee_A_Pixel-Level_Meta-Learner_for_Weakly_Supervised_Few-Shot_Semantic_Segmentation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Lee_A_Pixel-Level_Meta-Learner_for_Weakly_Supervised_Few-Shot_Semantic_Segmentation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Lee_A_Pixel-Level_Meta-Learner_WACV_2022_supplemental.pdf | 2111.01418 | cvf | @InProceedings{Lee_2022_WACV,
author = {Lee, Yuan-Hao and Yang, Fu-En and Wang, Yu-Chiang Frank},
title = {A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | Few-shot semantic segmentation addresses the learning task in which only few images with ground truth pixel-level labels are available for the novel classes of interest. One is typically required to collect a large mount of data (i.e., base classes) with such ground truth information, followed by meta-learning strategi... |
Cardace_Plugging_Self-Supervised_Monocular_Depth_Into_Unsupervised_Domain_Adaptation_for_Semantic_WACV_2022_paper | Plugging Self-Supervised Monocular Depth Into Unsupervised Domain Adaptation for Semantic Segmentation | [
"Adriano Cardace",
"Luca De Luigi",
"Pierluigi Zama Ramirez",
"Samuele Salti",
"Luigi Di Stefano"
] | https://openaccess.thecvf.com/content/WACV2022/html/Cardace_Plugging_Self-Supervised_Monocular_Depth_Into_Unsupervised_Domain_Adaptation_for_Semantic_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Cardace_Plugging_Self-Supervised_Monocular_Depth_Into_Unsupervised_Domain_Adaptation_for_Semantic_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Cardace_Plugging_Self-Supervised_Monocular_WACV_2022_supplemental.pdf | 2110.06685 | cvf | @InProceedings{Cardace_2022_WACV,
author = {Cardace, Adriano and De Luigi, Luca and Ramirez, Pierluigi Zama and Salti, Samuele and Di Stefano, Luigi},
title = {Plugging Self-Supervised Monocular Depth Into Unsupervised Domain Adaptation for Semantic Segmentation},
booktitle = {Proceedings of the IEEE... | Although recent semantic segmentation methods have made remarkable progress, they still rely on large amounts of annotated training data, which are often infeasible to collect in the autonomous driving scenario. Previous works usually tackle this issue with Unsupervised Domain Adaptation (UDA), which entails training a... |
Mustafa_Training_a_Task-Specific_Image_Reconstruction_Loss_WACV_2022_paper | Training a Task-Specific Image Reconstruction Loss | [
"Aamir Mustafa",
"Aliaksei Mikhailiuk",
"Dan Andrei Iliescu",
"Varun Babbar",
"Rafał K. Mantiuk"
] | https://openaccess.thecvf.com/content/WACV2022/html/Mustafa_Training_a_Task-Specific_Image_Reconstruction_Loss_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Mustafa_Training_a_Task-Specific_Image_Reconstruction_Loss_WACV_2022_paper.pdf | null | 2103.14616 | cvf | @InProceedings{Mustafa_2022_WACV,
author = {Mustafa, Aamir and Mikhailiuk, Aliaksei and Iliescu, Dan Andrei and Babbar, Varun and Mantiuk, Rafa{\l} K.},
title = {Training a Task-Specific Image Reconstruction Loss},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer... | The choice of a loss function is an important factor when training neural networks for image restoration problems, such as single image super resolution. The loss function should encourage natural and perceptually pleasing results. A popular choice for a loss is a pre-trained network, such as VGG, which is used as a fe... |
Yuan_Learning_to_Weight_Filter_Groups_for_Robust_Classification_WACV_2022_paper | Learning to Weight Filter Groups for Robust Classification | [
"Siyang Yuan",
"Yitong Li",
"Dong Wang",
"Ke Bai",
"Lawrence Carin",
"David Carlson"
] | https://openaccess.thecvf.com/content/WACV2022/html/Yuan_Learning_to_Weight_Filter_Groups_for_Robust_Classification_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Yuan_Learning_to_Weight_Filter_Groups_for_Robust_Classification_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Yuan_Learning_to_Weight_WACV_2022_supplemental.pdf | null | null | @InProceedings{Yuan_2022_WACV,
author = {Yuan, Siyang and Li, Yitong and Wang, Dong and Bai, Ke and Carin, Lawrence and Carlson, David},
title = {Learning to Weight Filter Groups for Robust Classification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision ... | In many real-world tasks, a canonical "big data" problem is created by combining data from several individual groups or domains. Because test data will likely come from a new group of data, we want to utilize the grouped structure of our training data to enforce generalization between groups of data, not just individua... |
Xiang_Adversarial_Open_Domain_Adaptation_for_Sketch-to-Photo_Synthesis_WACV_2022_paper | Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis | [
"Xiaoyu Xiang",
"Ding Liu",
"Xiao Yang",
"Yiheng Zhu",
"Xiaohui Shen",
"Jan P. Allebach"
] | https://openaccess.thecvf.com/content/WACV2022/html/Xiang_Adversarial_Open_Domain_Adaptation_for_Sketch-to-Photo_Synthesis_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Xiang_Adversarial_Open_Domain_Adaptation_for_Sketch-to-Photo_Synthesis_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Xiang_Adversarial_Open_Domain_WACV_2022_supplemental.pdf | 2104.05703 | cvf | @InProceedings{Xiang_2022_WACV,
author = {Xiang, Xiaoyu and Liu, Ding and Yang, Xiao and Zhu, Yiheng and Shen, Xiaohui and Allebach, Jan P.},
title = {Adversarial Open Domain Adaptation for Sketch-to-Photo Synthesis},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compu... | In this paper, we explore open-domain sketch-to-photo translation, which aims to synthesize a realistic photo from a freehand sketch with its class label, even if the sketches of that class are missing in the training data. It is challenging due to the lack of training supervision and the large geometric distortion bet... |
Sadekar_Shadow_Art_Revisited_A_Differentiable_Rendering_Based_Approach_WACV_2022_paper | Shadow Art Revisited: A Differentiable Rendering Based Approach | [
"Kaustubh Sadekar",
"Ashish Tiwari",
"Shanmuganathan Raman"
] | https://openaccess.thecvf.com/content/WACV2022/html/Sadekar_Shadow_Art_Revisited_A_Differentiable_Rendering_Based_Approach_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Sadekar_Shadow_Art_Revisited_A_Differentiable_Rendering_Based_Approach_WACV_2022_paper.pdf | null | 2107.14539 | cvf | @InProceedings{Sadekar_2022_WACV,
author = {Sadekar, Kaustubh and Tiwari, Ashish and Raman, Shanmuganathan},
title = {Shadow Art Revisited: A Differentiable Rendering Based Approach},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | While recent learning-based methods have been observed to be superior for several vision-related applications, their potential in generating artistic effects has not been explored much. One such exciting application is Shadow Art - a unique form of sculptural art that produces artistic effects through 2D shadows cast b... |
Tiwari_Occlusion_Resistant_Network_for_3D_Face_Reconstruction_WACV_2022_paper | Occlusion Resistant Network for 3D Face Reconstruction | [
"Hitika Tiwari",
"Vinod K. Kurmi",
"K.S. Venkatesh",
"Yong-Sheng Chen"
] | https://openaccess.thecvf.com/content/WACV2022/html/Tiwari_Occlusion_Resistant_Network_for_3D_Face_Reconstruction_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Tiwari_Occlusion_Resistant_Network_for_3D_Face_Reconstruction_WACV_2022_paper.pdf | null | null | null | @InProceedings{Tiwari_2022_WACV,
author = {Tiwari, Hitika and Kurmi, Vinod K. and Venkatesh, K.S. and Chen, Yong-Sheng},
title = {Occlusion Resistant Network for 3D Face Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | 3D face reconstruction from a monocular face image is a mathematically ill-posed problem. Recently, we observed a surge of interest in deep learning-based approaches to address the issue. These methods possess extreme sensitivity towards occlusions. Thus, in this paper, we present a novel context-learning-based distill... |
Abu-Hussein_Image_Restoration_by_Deep_Projected_GSURE_WACV_2022_paper | Image Restoration by Deep Projected GSURE | [
"Shady Abu-Hussein",
"Tom Tirer",
"Se Young Chun",
"Yonina C. Eldar",
"Raja Giryes"
] | https://openaccess.thecvf.com/content/WACV2022/html/Abu-Hussein_Image_Restoration_by_Deep_Projected_GSURE_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Abu-Hussein_Image_Restoration_by_Deep_Projected_GSURE_WACV_2022_paper.pdf | null | 2102.02485 | title_snapshot | @InProceedings{Abu-Hussein_2022_WACV,
author = {Abu-Hussein, Shady and Tirer, Tom and Chun, Se Young and Eldar, Yonina C. and Giryes, Raja},
title = {Image Restoration by Deep Projected GSURE},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Ill-posed inverse problems appear in many image processing applications, such as deblurring and super-resolution. In recent years, solutions that are based on deep Convolutional Neural Networks (CNNs) have shown great promise. Yet, most of these techniques, which train CNNs using external data, are restricted to the ob... |
Pramanick_Multimodal_Learning_Using_Optimal_Transport_for_Sarcasm_and_Humor_Detection_WACV_2022_paper | Multimodal Learning Using Optimal Transport for Sarcasm and Humor Detection | [
"Shraman Pramanick",
"Aniket Roy",
"Vishal M. Patel"
] | https://openaccess.thecvf.com/content/WACV2022/html/Pramanick_Multimodal_Learning_Using_Optimal_Transport_for_Sarcasm_and_Humor_Detection_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Pramanick_Multimodal_Learning_Using_Optimal_Transport_for_Sarcasm_and_Humor_Detection_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Pramanick_Multimodal_Learning_Using_WACV_2022_supplemental.pdf | 2110.10949 | cvf | @InProceedings{Pramanick_2022_WACV,
author = {Pramanick, Shraman and Roy, Aniket and Patel, Vishal M.},
title = {Multimodal Learning Using Optimal Transport for Sarcasm and Humor Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mon... | Multimodal learning is an emerging yet challenging research area. In this paper, we deal with multimodal sarcasm and humor detection from conversational videos and image-text pairs. Being a fleeting action, which is dependent across the modalities, sarcasm detection is challenging since large datasets are not available... |
Lugmayr_Normalizing_Flow_as_a_Flexible_Fidelity_Objective_for_Photo-Realistic_Super-Resolution_WACV_2022_paper | Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-Resolution | [
"Andreas Lugmayr",
"Martin Danelljan",
"Fisher Yu",
"Luc Van Gool",
"Radu Timofte"
] | https://openaccess.thecvf.com/content/WACV2022/html/Lugmayr_Normalizing_Flow_as_a_Flexible_Fidelity_Objective_for_Photo-Realistic_Super-Resolution_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Lugmayr_Normalizing_Flow_as_a_Flexible_Fidelity_Objective_for_Photo-Realistic_Super-Resolution_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Lugmayr_Normalizing_Flow_as_WACV_2022_supplemental.pdf | 2111.03649 | cvf | @InProceedings{Lugmayr_2022_WACV,
author = {Lugmayr, Andreas and Danelljan, Martin and Yu, Fisher and Van Gool, Luc and Timofte, Radu},
title = {Normalizing Flow as a Flexible Fidelity Objective for Photo-Realistic Super-Resolution},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Appli... | Super-resolution is an ill-posed problem, where a ground-truth high-resolution image represents only one possibility in the space of plausible solutions. Yet, the dominant paradigm is to employ pixel-wise losses, such as L_1, which drive the prediction towards a blurry average. This leads to fundamentally conflicting o... |
Zhao_Towards_Class-Oriented_Poisoning_Attacks_Against_Neural_Networks_WACV_2022_paper | Towards Class-Oriented Poisoning Attacks Against Neural Networks | [
"Bingyin Zhao",
"Yingjie Lao"
] | https://openaccess.thecvf.com/content/WACV2022/html/Zhao_Towards_Class-Oriented_Poisoning_Attacks_Against_Neural_Networks_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Zhao_Towards_Class-Oriented_Poisoning_Attacks_Against_Neural_Networks_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Zhao_Towards_Class-Oriented_Poisoning_WACV_2022_supplemental.pdf | 2008.00047 | cvf | @InProceedings{Zhao_2022_WACV,
author = {Zhao, Bingyin and Lao, Yingjie},
title = {Towards Class-Oriented Poisoning Attacks Against Neural Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022... | Poisoning attacks on machine learning systems compromise the model performance by deliberately injecting malicious samples in the training dataset to influence the training process. Prior works focus on either availability attacks (i.e., lowering the overall model accuracy) or integrity attacks (i.e., enabling specific... |
Chen_Transfer_Learning_for_Pose_Estimation_of_Illustrated_Characters_WACV_2022_paper | Transfer Learning for Pose Estimation of Illustrated Characters | [
"Shuhong Chen",
"Matthias Zwicker"
] | https://openaccess.thecvf.com/content/WACV2022/html/Chen_Transfer_Learning_for_Pose_Estimation_of_Illustrated_Characters_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Chen_Transfer_Learning_for_Pose_Estimation_of_Illustrated_Characters_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Chen_Transfer_Learning_for_WACV_2022_supplemental.zip | 2108.01819 | cvf | @InProceedings{Chen_2022_WACV,
author = {Chen, Shuhong and Zwicker, Matthias},
title = {Transfer Learning for Pose Estimation of Illustrated Characters},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {... | Human pose information is a critical component in many downstream image processing tasks, such as activity recognition and motion tracking. Likewise, a pose estimator for the illustrated character domain would provide a valuable prior for assistive content creation tasks, such as reference pose retrieval and automatic ... |
Nie_From_Node_To_Graph_Joint_Reasoning_on_Visual-Semantic_Relational_Graph_WACV_2022_paper | From Node To Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot Detection | [
"Hui Nie",
"Ruiping Wang",
"Xilin Chen"
] | https://openaccess.thecvf.com/content/WACV2022/html/Nie_From_Node_To_Graph_Joint_Reasoning_on_Visual-Semantic_Relational_Graph_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Nie_From_Node_To_Graph_Joint_Reasoning_on_Visual-Semantic_Relational_Graph_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Nie_From_Node_To_WACV_2022_supplemental.pdf | null | null | @InProceedings{Nie_2022_WACV,
author = {Nie, Hui and Wang, Ruiping and Chen, Xilin},
title = {From Node To Graph: Joint Reasoning on Visual-Semantic Relational Graph for Zero-Shot Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mo... | Zero-Shot Detection (ZSD), which aims at localizing and recognizing unseen objects in a complicated scene, usually leverages the visual and semantic information of individual objects alone. However, scene understanding of human exceeds recognizing individual objects separately: the contextual information among multiple... |
Shi_Unsupervised_Sounding_Object_Localization_With_Bottom-Up_and_Top-Down_Attention_WACV_2022_paper | Unsupervised Sounding Object Localization With Bottom-Up and Top-Down Attention | [
"Jiayin Shi",
"Chao Ma"
] | https://openaccess.thecvf.com/content/WACV2022/html/Shi_Unsupervised_Sounding_Object_Localization_With_Bottom-Up_and_Top-Down_Attention_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Shi_Unsupervised_Sounding_Object_Localization_With_Bottom-Up_and_Top-Down_Attention_WACV_2022_paper.pdf | null | null | null | @InProceedings{Shi_2022_WACV,
author = {Shi, Jiayin and Ma, Chao},
title = {Unsupervised Sounding Object Localization With Bottom-Up and Top-Down Attention},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Learning to localize sounding objects in visual scenes without manual annotations has drawn increasing attention recently. In this paper, we propose an unsupervised sounding object localization algorithm by using bottom-up and top-down attention in visual scenes. The bottom-up attention module generates an objectness c... |
Tsai_Multi-Scale_Patch-Based_Representation_Learning_for_Image_Anomaly_Detection_and_Segmentation_WACV_2022_paper | Multi-Scale Patch-Based Representation Learning for Image Anomaly Detection and Segmentation | [
"Chin-Chia Tsai",
"Tsung-Hsuan Wu",
"Shang-Hong Lai"
] | https://openaccess.thecvf.com/content/WACV2022/html/Tsai_Multi-Scale_Patch-Based_Representation_Learning_for_Image_Anomaly_Detection_and_Segmentation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Tsai_Multi-Scale_Patch-Based_Representation_Learning_for_Image_Anomaly_Detection_and_Segmentation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Tsai_Multi-Scale_Patch-Based_Representation_WACV_2022_supplemental.pdf | null | null | @InProceedings{Tsai_2022_WACV,
author = {Tsai, Chin-Chia and Wu, Tsung-Hsuan and Lai, Shang-Hong},
title = {Multi-Scale Patch-Based Representation Learning for Image Anomaly Detection and Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WAC... | Unsupervised representation learning has been proven to be effective for the challenging anomaly detection and segmentation tasks. In this paper, we propose a multi-scale patch-based representation learning method to extract critical and representative information from normal images. By taking the relative feature simi... |
Fobi_Predicting_Levels_of_Household_Electricity_Consumption_in_Low-Access_Settings_WACV_2022_paper | Predicting Levels of Household Electricity Consumption in Low-Access Settings | [
"Simone Fobi",
"Joel Mugyenyi",
"Nathaniel J. Williams",
"Vijay Modi",
"Jay Taneja"
] | https://openaccess.thecvf.com/content/WACV2022/html/Fobi_Predicting_Levels_of_Household_Electricity_Consumption_in_Low-Access_Settings_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Fobi_Predicting_Levels_of_Household_Electricity_Consumption_in_Low-Access_Settings_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Fobi_Predicting_Levels_of_WACV_2022_supplemental.pdf | 2112.08497 | cvf | @InProceedings{Fobi_2022_WACV,
author = {Fobi, Simone and Mugyenyi, Joel and Williams, Nathaniel J. and Modi, Vijay and Taneja, Jay},
title = {Predicting Levels of Household Electricity Consumption in Low-Access Settings},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of ... | In low-income settings, the most critical piece of information for electric utilities is the anticipated consumption of a customer. Electricity consumption assessment is difficult to do in settings where a significant fraction of households do not yet have an electricity connection. In such settings the absolute levels... |
Kaya_Neural_Radiance_Fields_Approach_to_Deep_Multi-View_Photometric_Stereo_WACV_2022_paper | Neural Radiance Fields Approach to Deep Multi-View Photometric Stereo | [
"Berk Kaya",
"Suryansh Kumar",
"Francesco Sarno",
"Vittorio Ferrari",
"Luc Van Gool"
] | https://openaccess.thecvf.com/content/WACV2022/html/Kaya_Neural_Radiance_Fields_Approach_to_Deep_Multi-View_Photometric_Stereo_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Kaya_Neural_Radiance_Fields_Approach_to_Deep_Multi-View_Photometric_Stereo_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Kaya_Neural_Radiance_Fields_WACV_2022_supplemental.zip | 2110.05594 | cvf | @InProceedings{Kaya_2022_WACV,
author = {Kaya, Berk and Kumar, Suryansh and Sarno, Francesco and Ferrari, Vittorio and Van Gool, Luc},
title = {Neural Radiance Fields Approach to Deep Multi-View Photometric Stereo},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compute... | We present a modern solution to the multi-view photometric stereo problem (MVPS). Our work suitably exploits the image formation model in a MVPS experimental setup to recover the dense 3D reconstruction of an object from images. We procure the surface orientation using a photometric stereo (PS) image formation model an... |
Wang_Post-OCR_Paragraph_Recognition_by_Graph_Convolutional_Networks_WACV_2022_paper | Post-OCR Paragraph Recognition by Graph Convolutional Networks | [
"Renshen Wang",
"Yasuhisa Fujii",
"Ashok C. Popat"
] | https://openaccess.thecvf.com/content/WACV2022/html/Wang_Post-OCR_Paragraph_Recognition_by_Graph_Convolutional_Networks_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Wang_Post-OCR_Paragraph_Recognition_by_Graph_Convolutional_Networks_WACV_2022_paper.pdf | null | 2101.12741 | cvf | @InProceedings{Wang_2022_WACV,
author = {Wang, Renshen and Fujii, Yasuhisa and Popat, Ashok C.},
title = {Post-OCR Paragraph Recognition by Graph Convolutional Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | We propose a new approach for paragraph recognition in document images by spatial graph convolutional networks (GCN) applied on OCR text boxes. Two steps, namely line splitting and line clustering, are performed to extract paragraphs from the lines in OCR results. Each step uses a beta-skeleton graph constructed from b... |
Scheliga_PRECODE_-_A_Generic_Model_Extension_To_Prevent_Deep_Gradient_WACV_2022_paper | PRECODE - A Generic Model Extension To Prevent Deep Gradient Leakage | [
"Daniel Scheliga",
"Patrick Mäder",
"Marco Seeland"
] | https://openaccess.thecvf.com/content/WACV2022/html/Scheliga_PRECODE_-_A_Generic_Model_Extension_To_Prevent_Deep_Gradient_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Scheliga_PRECODE_-_A_Generic_Model_Extension_To_Prevent_Deep_Gradient_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Scheliga_PRECODE_-_A_WACV_2022_supplemental.pdf | 2108.04725 | title_snapshot | @InProceedings{Scheliga_2022_WACV,
author = {Scheliga, Daniel and M\"ader, Patrick and Seeland, Marco},
title = {PRECODE - A Generic Model Extension To Prevent Deep Gradient Leakage},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Collaborative training of neural networks leverages distributed data by exchanging gradient information between different clients. Although training data entirely resides with the clients, recent work shows that training data can be reconstructed from such exchanged gradient information. To enhance privacy, gradient pe... |
Bashkirova_Evaluation_of_Correctness_in_Unsupervised_Many-to-Many_Image_Translation_WACV_2022_paper | Evaluation of Correctness in Unsupervised Many-to-Many Image Translation | [
"Dina Bashkirova",
"Ben Usman",
"Kate Saenko"
] | https://openaccess.thecvf.com/content/WACV2022/html/Bashkirova_Evaluation_of_Correctness_in_Unsupervised_Many-to-Many_Image_Translation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Bashkirova_Evaluation_of_Correctness_in_Unsupervised_Many-to-Many_Image_Translation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Bashkirova_Evaluation_of_Correctness_WACV_2022_supplemental.pdf | 2103.15727 | cvf | @InProceedings{Bashkirova_2022_WACV,
author = {Bashkirova, Dina and Usman, Ben and Saenko, Kate},
title = {Evaluation of Correctness in Unsupervised Many-to-Many Image Translation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = ... | Given an input image from a source domain and a guidance image from a target domain, unsupervised many-to-many image-to-image (UMMI2I) translation methods seek to generate a plausible example from the target domain that preserves domain-invariant information of the input source image and inherits the domain-specific in... |
Mall_Discovering_Underground_Maps_From_Fashion_WACV_2022_paper | Discovering Underground Maps From Fashion | [
"Utkarsh Mall",
"Kavita Bala",
"Tamara Berg",
"Kristen Grauman"
] | https://openaccess.thecvf.com/content/WACV2022/html/Mall_Discovering_Underground_Maps_From_Fashion_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Mall_Discovering_Underground_Maps_From_Fashion_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Mall_Discovering_Underground_Maps_WACV_2022_supplemental.zip | 2012.02897 | cvf | @InProceedings{Mall_2022_WACV,
author = {Mall, Utkarsh and Bala, Kavita and Berg, Tamara and Grauman, Kristen},
title = {Discovering Underground Maps From Fashion},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
ye... | The fashion sense--meaning the clothing styles people wear--in a geographical region can reveal information about that region. For example, it can reflect the kind of activities people do there, or the type of crowds that frequently visit the region (e.g., tourist hot spot, student neighborhood, business center). We pr... |
Lamba_Fast_and_Efficient_Restoration_of_Extremely_Dark_Light_Fields_WACV_2022_paper | Fast and Efficient Restoration of Extremely Dark Light Fields | [
"Mohit Lamba",
"Kaushik Mitra"
] | https://openaccess.thecvf.com/content/WACV2022/html/Lamba_Fast_and_Efficient_Restoration_of_Extremely_Dark_Light_Fields_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Lamba_Fast_and_Efficient_Restoration_of_Extremely_Dark_Light_Fields_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Lamba_Fast_and_Efficient_WACV_2022_supplemental.zip | null | null | @InProceedings{Lamba_2022_WACV,
author = {Lamba, Mohit and Mitra, Kaushik},
title = {Fast and Efficient Restoration of Extremely Dark Light Fields},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022}... | The ability of Light Field (LF) cameras to capture the 3D geometry of a scene in a single photographic exposure has become central to several applications ranging from passive depth estimation to autonomous driving. But these applications cannot rely on LF captured in low-light conditions due to excessive noise and poo... |
Peng_HERS_Superpixels_Deep_Affinity_Learning_for_Hierarchical_Entropy_Rate_Segmentation_WACV_2022_paper | HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation | [
"Hankui Peng",
"Angelica I. Aviles-Rivero",
"Carola-Bibiane Schönlieb"
] | https://openaccess.thecvf.com/content/WACV2022/html/Peng_HERS_Superpixels_Deep_Affinity_Learning_for_Hierarchical_Entropy_Rate_Segmentation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Peng_HERS_Superpixels_Deep_Affinity_Learning_for_Hierarchical_Entropy_Rate_Segmentation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Peng_HERS_Superpixels_Deep_WACV_2022_supplemental.pdf | 2106.03755 | title_snapshot | @InProceedings{Peng_2022_WACV,
author = {Peng, Hankui and Aviles-Rivero, Angelica I. and Sch\"onlieb, Carola-Bibiane},
title = {HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer ... | Superpixels serve as a powerful preprocessing tool in many computer vision tasks. By using superpixel representation, the number of image primitives can be largely reduced by orders of magnitudes. The majority of superpixel methods use handcrafted features, which usually do not translate well into strong adherence to o... |
Wan_Approximate_Neural_Architecture_Search_via_Operation_Distribution_Learning_WACV_2022_paper | Approximate Neural Architecture Search via Operation Distribution Learning | [
"Xingchen Wan",
"Binxin Ru",
"Pedro M. Esparança",
"Fabio Maria Carlucci"
] | https://openaccess.thecvf.com/content/WACV2022/html/Wan_Approximate_Neural_Architecture_Search_via_Operation_Distribution_Learning_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Wan_Approximate_Neural_Architecture_Search_via_Operation_Distribution_Learning_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Wan_Approximate_Neural_Architecture_WACV_2022_supplemental.pdf | 2111.04670 | title_snapshot | @InProceedings{Wan_2022_WACV,
author = {Wan, Xingchen and Ru, Binxin and Esparan\c{c}a, Pedro M. and Carlucci, Fabio Maria},
title = {Approximate Neural Architecture Search via Operation Distribution Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vis... | The standard paradigm in neural architecture search (NAS) is to search for a fully deterministic architecture with specific operations and connections. In this work, we instead propose to search for the optimal operation distribution, thus providing a stochastic and approximate solution, which can be used to sample arc... |
Lohit_Model_Compression_Using_Optimal_Transport_WACV_2022_paper | Model Compression Using Optimal Transport | [
"Suhas Lohit",
"Michael Jones"
] | https://openaccess.thecvf.com/content/WACV2022/html/Lohit_Model_Compression_Using_Optimal_Transport_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Lohit_Model_Compression_Using_Optimal_Transport_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Lohit_Model_Compression_Using_WACV_2022_supplemental.pdf | 2012.03907 | cvf | @InProceedings{Lohit_2022_WACV,
author = {Lohit, Suhas and Jones, Michael},
title = {Model Compression Using Optimal Transport},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pages = {2... | Model compression methods are important to allow for easier deployment of deep learning models in compute, memory and energy-constrained environments such as mobile phones. Knowledge distillation is a class of model compression algorithms where knowledge from a large teacher network is transferred to a smaller student ... |
Hou_Multi-Dimensional_Dynamic_Model_Compression_for_Efficient_Image_Super-Resolution_WACV_2022_paper | Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution | [
"Zejiang Hou",
"Sun-Yuan Kung"
] | https://openaccess.thecvf.com/content/WACV2022/html/Hou_Multi-Dimensional_Dynamic_Model_Compression_for_Efficient_Image_Super-Resolution_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Hou_Multi-Dimensional_Dynamic_Model_Compression_for_Efficient_Image_Super-Resolution_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Hou_Multi-Dimensional_Dynamic_Model_WACV_2022_supplemental.pdf | null | null | @InProceedings{Hou_2022_WACV,
author = {Hou, Zejiang and Kung, Sun-Yuan},
title = {Multi-Dimensional Dynamic Model Compression for Efficient Image Super-Resolution},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
y... | Modern single image super-resolution (SR) system based on convolutional neural networks achieves substantial progress. However, most SR deep networks are computationally expensive and require excessively large activation memory footprints, impeding their effective deployment to resource-limited devices. Based on the ob... |
Wang_Disentangled_Representation_With_Dual-Stage_Feature_Learning_for_Face_Anti-Spoofing_WACV_2022_paper | Disentangled Representation With Dual-Stage Feature Learning for Face Anti-Spoofing | [
"Yu-Chun Wang",
"Chien-Yi Wang",
"Shang-Hong Lai"
] | https://openaccess.thecvf.com/content/WACV2022/html/Wang_Disentangled_Representation_With_Dual-Stage_Feature_Learning_for_Face_Anti-Spoofing_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Wang_Disentangled_Representation_With_Dual-Stage_Feature_Learning_for_Face_Anti-Spoofing_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Wang_Disentangled_Representation_With_WACV_2022_supplemental.pdf | 2110.09157 | cvf | @InProceedings{Wang_2022_WACV,
author = {Wang, Yu-Chun and Wang, Chien-Yi and Lai, Shang-Hong},
title = {Disentangled Representation With Dual-Stage Feature Learning for Face Anti-Spoofing},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mon... | As face recognition is widely used in diverse security-critical applications, the study of face anti-spoofing (FAS) has attracted more and more attention. Several FAS methods have achieved promising performances if the attack types in the testing data are the same as training data, while the performance significantly d... |
Leotta_On_the_Maximum_Radius_of_Polynomial_Lens_Distortion_WACV_2022_paper | On the Maximum Radius of Polynomial Lens Distortion | [
"Matthew J. Leotta",
"David Russell",
"Andrew Matrai"
] | https://openaccess.thecvf.com/content/WACV2022/html/Leotta_On_the_Maximum_Radius_of_Polynomial_Lens_Distortion_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Leotta_On_the_Maximum_Radius_of_Polynomial_Lens_Distortion_WACV_2022_paper.pdf | null | null | null | @InProceedings{Leotta_2022_WACV,
author = {Leotta, Matthew J. and Russell, David and Matrai, Andrew},
title = {On the Maximum Radius of Polynomial Lens Distortion},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
ye... | Polynomial radial lens distortion models are widely used in image processing and computer vision applications to compensate for when straight lines in the world appear curved in an image. While polynomial models are used pervasively in software ranging from PhotoShop to OpenCV to Blender, they have an often overlooked ... |
Kumar_Generative_Adversarial_Attack_on_Ensemble_Clustering_WACV_2022_paper | Generative Adversarial Attack on Ensemble Clustering | [
"Chetan Kumar",
"Deepak Kumar",
"Ming Shao"
] | https://openaccess.thecvf.com/content/WACV2022/html/Kumar_Generative_Adversarial_Attack_on_Ensemble_Clustering_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Kumar_Generative_Adversarial_Attack_on_Ensemble_Clustering_WACV_2022_paper.pdf | null | null | null | @InProceedings{Kumar_2022_WACV,
author = {Kumar, Chetan and Kumar, Deepak and Shao, Ming},
title = {Generative Adversarial Attack on Ensemble Clustering},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = ... | Adversarial attack on learning tasks has attracted substantial attention in recent years; however, most existing works focus on supervised learning. Recently, research has shown that unsupervised learning, such as clustering, tends to be vulnerable due to adversarial attack. In this paper, we focus on a clustering algo... |
Sipka_The_Hitchhikers_Guide_to_Prior-Shift_Adaptation_WACV_2022_paper | The Hitchhiker's Guide to Prior-Shift Adaptation | [
"Tomáš Šipka",
"Milan Šulc",
"Jiří Matas"
] | https://openaccess.thecvf.com/content/WACV2022/html/Sipka_The_Hitchhikers_Guide_to_Prior-Shift_Adaptation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Sipka_The_Hitchhikers_Guide_to_Prior-Shift_Adaptation_WACV_2022_paper.pdf | null | 2106.11695 | title_snapshot | @InProceedings{Sipka_2022_WACV,
author = {\v{S}ipka, Tom\'a\v{s} and \v{S}ulc, Milan and Matas, Ji\v{r}{\'\i}},
title = {The Hitchhiker's Guide to Prior-Shift Adaptation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},... | In many computer vision classification tasks, class priors at test time often differ from priors on the training set. In the case of such prior shift, classifiers must be adapted correspondingly to maintain close to optimal performance. This paper analyzes methods for adaptation of probabilistic classifiers to new prio... |
Zhang_Hierarchically_Decoupled_Spatial-Temporal_Contrast_for_Self-Supervised_Video_Representation_Learning_WACV_2022_paper | Hierarchically Decoupled Spatial-Temporal Contrast for Self-Supervised Video Representation Learning | [
"Zehua Zhang",
"David Crandall"
] | https://openaccess.thecvf.com/content/WACV2022/html/Zhang_Hierarchically_Decoupled_Spatial-Temporal_Contrast_for_Self-Supervised_Video_Representation_Learning_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Zhang_Hierarchically_Decoupled_Spatial-Temporal_Contrast_for_Self-Supervised_Video_Representation_Learning_WACV_2022_paper.pdf | null | 2011.11261 | cvf | @InProceedings{Zhang_2022_WACV,
author = {Zhang, Zehua and Crandall, David},
title = {Hierarchically Decoupled Spatial-Temporal Contrast for Self-Supervised Video Representation Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | We present a novel technique for self-supervised video representation learning by: (a) decoupling the learning objective into two contrastive subtasks respectively emphasizing spatial and temporal features, and (b) performing it hierarchically to encourage multi-scale understanding. Motivated by their effectiveness in ... |
Khodadadeh_Latent_to_Latent_A_Learned_Mapper_for_Identity_Preserving_Editing_WACV_2022_paper | Latent to Latent: A Learned Mapper for Identity Preserving Editing of Multiple Face Attributes in StyleGAN-Generated Images | [
"Siavash Khodadadeh",
"Shabnam Ghadar",
"Saeid Motiian",
"Wei-An Lin",
"Ladislau Bölöni",
"Ratheesh Kalarot"
] | https://openaccess.thecvf.com/content/WACV2022/html/Khodadadeh_Latent_to_Latent_A_Learned_Mapper_for_Identity_Preserving_Editing_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Khodadadeh_Latent_to_Latent_A_Learned_Mapper_for_Identity_Preserving_Editing_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Khodadadeh_Latent_to_Latent_WACV_2022_supplemental.pdf | null | null | @InProceedings{Khodadadeh_2022_WACV,
author = {Khodadadeh, Siavash and Ghadar, Shabnam and Motiian, Saeid and Lin, Wei-An and B\"ol\"oni, Ladislau and Kalarot, Ratheesh},
title = {Latent to Latent: A Learned Mapper for Identity Preserving Editing of Multiple Face Attributes in StyleGAN-Generated Images},... | Several recent papers introduced techniques to adjust the attributes of human faces generated by unconditional GANs such as StyleGAN. Despite efforts to disentangle the attributes, a request to change one attribute often triggers unwanted changes to other attributes as well. More importantly, in some cases, a human obs... |
Yang_Dynamic_Iterative_Refinement_for_Efficient_3D_Hand_Pose_Estimation_WACV_2022_paper | Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation | [
"John Yang",
"Yash Bhalgat",
"Simyung Chang",
"Fatih Porikli",
"Nojun Kwak"
] | https://openaccess.thecvf.com/content/WACV2022/html/Yang_Dynamic_Iterative_Refinement_for_Efficient_3D_Hand_Pose_Estimation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Yang_Dynamic_Iterative_Refinement_for_Efficient_3D_Hand_Pose_Estimation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Yang_Dynamic_Iterative_Refinement_WACV_2022_supplemental.pdf | 2111.06500 | cvf | @InProceedings{Yang_2022_WACV,
author = {Yang, John and Bhalgat, Yash and Chang, Simyung and Porikli, Fatih and Kwak, Nojun},
title = {Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WA... | While hand pose estimation is a critical component of most interactive extended reality and gesture recognition systems, contemporary approaches are not optimized for computational and memory efficiency. In this paper, we propose a tiny deep neural network of which partial layers are recursively exploited for refining ... |
Jeevan_Resource-Efficient_Hybrid_X-Formers_for_Vision_WACV_2022_paper | Resource-Efficient Hybrid X-Formers for Vision | [
"Pranav Jeevan",
"Amit Sethi"
] | https://openaccess.thecvf.com/content/WACV2022/html/Jeevan_Resource-Efficient_Hybrid_X-Formers_for_Vision_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Jeevan_Resource-Efficient_Hybrid_X-Formers_for_Vision_WACV_2022_paper.pdf | null | null | null | @InProceedings{Jeevan_2022_WACV,
author = {Jeevan, Pranav and Sethi, Amit},
title = {Resource-Efficient Hybrid X-Formers for Vision},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pages ... | Although transformers have become the neural architectures of choice for natural language processing, they require orders of magnitude more training data, GPU memory, and computations in order to compete with convolutional neural networks for computer vision. The attention mechanism of transformers scales quadratically... |
Uddin_Quantified_Facial_Expressiveness_for_Affective_Behavior_Analytics_WACV_2022_paper | Quantified Facial Expressiveness for Affective Behavior Analytics | [
"Md Taufeeq Uddin",
"Shaun Canavan"
] | https://openaccess.thecvf.com/content/WACV2022/html/Uddin_Quantified_Facial_Expressiveness_for_Affective_Behavior_Analytics_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Uddin_Quantified_Facial_Expressiveness_for_Affective_Behavior_Analytics_WACV_2022_paper.pdf | null | 2110.01758 | cvf | @InProceedings{Uddin_2022_WACV,
author = {Uddin, Md Taufeeq and Canavan, Shaun},
title = {Quantified Facial Expressiveness for Affective Behavior Analytics},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | The quantified measurement of facial expressiveness is crucial to analyze human affective behavior at scale. Unfortunately, methods for expressiveness quantification at the video frame-level are largely unexplored, unlike the study of discrete expression. In this work, we propose an algorithm that quantifies facial exp... |
Xu_FalCon_Fine-Grained_Feature_Map_Sparsity_Computing_With_Decomposed_Convolutions_for_WACV_2022_paper | FalCon: Fine-Grained Feature Map Sparsity Computing With Decomposed Convolutions for Inference Optimization | [
"Zirui Xu",
"Fuxun Yu",
"Chenxi Liu",
"Zhe Wu",
"Hongcheng Wang",
"Xiang Chen"
] | https://openaccess.thecvf.com/content/WACV2022/html/Xu_FalCon_Fine-Grained_Feature_Map_Sparsity_Computing_With_Decomposed_Convolutions_for_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Xu_FalCon_Fine-Grained_Feature_Map_Sparsity_Computing_With_Decomposed_Convolutions_for_WACV_2022_paper.pdf | null | null | null | @InProceedings{Xu_2022_WACV,
author = {Xu, Zirui and Yu, Fuxun and Liu, Chenxi and Wu, Zhe and Wang, Hongcheng and Chen, Xiang},
title = {FalCon: Fine-Grained Feature Map Sparsity Computing With Decomposed Convolutions for Inference Optimization},
booktitle = {Proceedings of the IEEE/CVF Winter Confe... | Many works focus on the model's static parameter optimization (e.g., filters and weights) for CNN inference acceleration. Compared to parameter sparsity, feature map sparsity is per-input related which has better adaptability. The practical sparsity patterns are non-structural and randomly located on feature maps with ... |
Horvath_METGAN_Generative_Tumour_Inpainting_and_Modality_Synthesis_in_Light_Sheet_WACV_2022_paper | METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy | [
"Izabela Horvath",
"Johannes Paetzold",
"Oliver Schoppe",
"Rami Al-Maskari",
"Ivan Ezhov",
"Suprosanna Shit",
"Hongwei Li",
"Ali Ertürk",
"Bjoern Menze"
] | https://openaccess.thecvf.com/content/WACV2022/html/Horvath_METGAN_Generative_Tumour_Inpainting_and_Modality_Synthesis_in_Light_Sheet_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Horvath_METGAN_Generative_Tumour_Inpainting_and_Modality_Synthesis_in_Light_Sheet_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Horvath_METGAN_Generative_Tumour_WACV_2022_supplemental.pdf | 2104.10993 | cvf | @InProceedings{Horvath_2022_WACV,
author = {Horvath, Izabela and Paetzold, Johannes and Schoppe, Oliver and Al-Maskari, Rami and Ezhov, Ivan and Shit, Suprosanna and Li, Hongwei and Ert\"urk, Ali and Menze, Bjoern},
title = {METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Micro... | Novel multimodal imaging methods are capable of generating extensive, super high resolution datasets for preclinical research. Yet, a massive lack of annotations prevents the broad use of deep learning to analyze such data. In this paper, we introduce a novel generative method which leverages real anatomical informatio... |
Emad_MoESR_Blind_Super-Resolution_Using_Kernel-Aware_Mixture_of_Experts_WACV_2022_paper | MoESR: Blind Super-Resolution Using Kernel-Aware Mixture of Experts | [
"Mohammad Emad",
"Maurice Peemen",
"Henk Corporaal"
] | https://openaccess.thecvf.com/content/WACV2022/html/Emad_MoESR_Blind_Super-Resolution_Using_Kernel-Aware_Mixture_of_Experts_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Emad_MoESR_Blind_Super-Resolution_Using_Kernel-Aware_Mixture_of_Experts_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Emad_MoESR_Blind_Super-Resolution_WACV_2022_supplemental.pdf | null | null | @InProceedings{Emad_2022_WACV,
author = {Emad, Mohammad and Peemen, Maurice and Corporaal, Henk},
title = {MoESR: Blind Super-Resolution Using Kernel-Aware Mixture of Experts},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Janu... | Modern deep learning super-resolution approaches have achieved remarkable performance where the low-resolution (LR) input is a degraded high-resolution (HR) image by a fixed known kernel i.e. kernel-specific super-resolution (SR). However, real images often vary in their degradation kernels, thus a single kernel-specif... |
Wei_Spatial-Temporal_Transformer_for_3D_Point_Cloud_Sequences_WACV_2022_paper | Spatial-Temporal Transformer for 3D Point Cloud Sequences | [
"Yimin Wei",
"Hao Liu",
"Tingting Xie",
"Qiuhong Ke",
"Yulan Guo"
] | https://openaccess.thecvf.com/content/WACV2022/html/Wei_Spatial-Temporal_Transformer_for_3D_Point_Cloud_Sequences_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Wei_Spatial-Temporal_Transformer_for_3D_Point_Cloud_Sequences_WACV_2022_paper.pdf | null | 2110.09783 | cvf | @InProceedings{Wei_2022_WACV,
author = {Wei, Yimin and Liu, Hao and Xie, Tingting and Ke, Qiuhong and Guo, Yulan},
title = {Spatial-Temporal Transformer for 3D Point Cloud Sequences},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Effective learning of spatial-temporal information within a point cloud sequence is highly important for many down-stream tasks such as 4D semantic segmentation and 3D action recognition. In this paper, we propose a novel framework named Point Spatial-Temporal Transformer (PST2) to learn spatial-temporal representation... |
Dhingra_LwPosr_Lightweight_Efficient_Fine_Grained_Head_Pose_Estimation_WACV_2022_paper | LwPosr: Lightweight Efficient Fine Grained Head Pose Estimation | [
"Naina Dhingra"
] | https://openaccess.thecvf.com/content/WACV2022/html/Dhingra_LwPosr_Lightweight_Efficient_Fine_Grained_Head_Pose_Estimation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Dhingra_LwPosr_Lightweight_Efficient_Fine_Grained_Head_Pose_Estimation_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Dhingra_LwPosr_Lightweight_Efficient_WACV_2022_supplemental.pdf | 2202.03544 | title_snapshot | @InProceedings{Dhingra_2022_WACV,
author = {Dhingra, Naina},
title = {LwPosr: Lightweight Efficient Fine Grained Head Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pages ... | This paper presents a lightweight network for head pose estimation (HPE) task. While previous approaches rely on convolutional neural networks, the proposed network LwPosr uses mixture of depthwise separable convolutional (DSC) and transformer encoder layers which are structured in two streams and three stages to provi... |
Kobayashi_Extractive_Knowledge_Distillation_WACV_2022_paper | Extractive Knowledge Distillation | [
"Takumi Kobayashi"
] | https://openaccess.thecvf.com/content/WACV2022/html/Kobayashi_Extractive_Knowledge_Distillation_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Kobayashi_Extractive_Knowledge_Distillation_WACV_2022_paper.pdf | null | null | null | @InProceedings{Kobayashi_2022_WACV,
author = {Kobayashi, Takumi},
title = {Extractive Knowledge Distillation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pages = {3511-3520}
} | Knowledge distillation (KD) transfers knowledge of a teacher model to improve performance of a student model which is usually equipped with lower capacity. In the KD framework, however, it is unclear what kind of knowledge is effective and how it is transferred. This paper analyzes a KD process to explore the key facto... |
Yu_Hessian-Aware_Pruning_and_Optimal_Neural_Implant_WACV_2022_paper | Hessian-Aware Pruning and Optimal Neural Implant | [
"Shixing Yu",
"Zhewei Yao",
"Amir Gholami",
"Zhen Dong",
"Sehoon Kim",
"Michael W. Mahoney",
"Kurt Keutzer"
] | https://openaccess.thecvf.com/content/WACV2022/html/Yu_Hessian-Aware_Pruning_and_Optimal_Neural_Implant_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Yu_Hessian-Aware_Pruning_and_Optimal_Neural_Implant_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Yu_Hessian-Aware_Pruning_and_WACV_2022_supplemental.pdf | 2101.08940 | cvf | @InProceedings{Yu_2022_WACV,
author = {Yu, Shixing and Yao, Zhewei and Gholami, Amir and Dong, Zhen and Kim, Sehoon and Mahoney, Michael W. and Keutzer, Kurt},
title = {Hessian-Aware Pruning and Optimal Neural Implant},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Com... | Pruning is an effective method to reduce the memory footprint and FLOPs associated with neural network models. However, existing structured pruning methods often result in significant accuracy degradation for moderate pruning levels. To address this problem, we introduce a new Hessian Aware Pruning (HAP) method coupled... |
Li_PERF-Net_Pose_Empowered_RGB-Flow_Net_WACV_2022_paper | PERF-Net: Pose Empowered RGB-Flow Net | [
"Yinxiao Li",
"Zhichao Lu",
"Xuehan Xiong",
"Jonathan Huang"
] | https://openaccess.thecvf.com/content/WACV2022/html/Li_PERF-Net_Pose_Empowered_RGB-Flow_Net_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Li_PERF-Net_Pose_Empowered_RGB-Flow_Net_WACV_2022_paper.pdf | null | 2009.13087 | title_snapshot | @InProceedings{Li_2022_WACV,
author = {Li, Yinxiao and Lu, Zhichao and Xiong, Xuehan and Huang, Jonathan},
title = {PERF-Net: Pose Empowered RGB-Flow Net},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year =... | In recent years, many works in the video action recognition literature have shown that two stream models (combining spatial and temporal input streams) are necessary for achieving state-of-the-art performance. In this paper we show the benefits of including yet another stream based on human pose estimated from each fra... |
Furukawa_Single-Shot_Dense_Active_Stereo_With_Pixel-Wise_Phase_Estimation_Based_on_WACV_2022_paper | Single-Shot Dense Active Stereo With Pixel-Wise Phase Estimation Based on Grid-Structure Using CNN and Correspondence Estimation Using GCN | [
"Ryo Furukawa",
"Michihiro Mikamo",
"Ryusuke Sagawa",
"Hiroshi Kawasaki"
] | https://openaccess.thecvf.com/content/WACV2022/html/Furukawa_Single-Shot_Dense_Active_Stereo_With_Pixel-Wise_Phase_Estimation_Based_on_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Furukawa_Single-Shot_Dense_Active_Stereo_With_Pixel-Wise_Phase_Estimation_Based_on_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Furukawa_Single-Shot_Dense_Active_WACV_2022_supplemental.zip | null | null | @InProceedings{Furukawa_2022_WACV,
author = {Furukawa, Ryo and Mikamo, Michihiro and Sagawa, Ryusuke and Kawasaki, Hiroshi},
title = {Single-Shot Dense Active Stereo With Pixel-Wise Phase Estimation Based on Grid-Structure Using CNN and Correspondence Estimation Using GCN},
booktitle = {Proceedings o... | Active stereo systems based on static pattern projection,a.k.a. oneshot scan, have been widely used for measuring dynamic scenes. Many patterns used for oneshot active stereo have grid structures and grid-wise codes. For such systems, the grid structure is first detected, and graph matching methods are applied to estim... |
Li_NUTA_Non-Uniform_Temporal_Aggregation_for_Action_Recognition_WACV_2022_paper | NUTA: Non-Uniform Temporal Aggregation for Action Recognition | [
"Xinyu Li",
"Chunhui Liu",
"Bing Shuai",
"Yi Zhu",
"Hao Chen",
"Joseph Tighe"
] | https://openaccess.thecvf.com/content/WACV2022/html/Li_NUTA_Non-Uniform_Temporal_Aggregation_for_Action_Recognition_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Li_NUTA_Non-Uniform_Temporal_Aggregation_for_Action_Recognition_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Li_NUTA_Non-Uniform_Temporal_WACV_2022_supplemental.pdf | 2012.08041 | cvf | @InProceedings{Li_2022_WACV,
author = {Li, Xinyu and Liu, Chunhui and Shuai, Bing and Zhu, Yi and Chen, Hao and Tighe, Joseph},
title = {NUTA: Non-Uniform Temporal Aggregation for Action Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)... | In the world of action recognition research, one primary focus has been on how to construct and train networks to model the spatial-temporal volume of an input video. These methods typically uniformly sample a segment of an input clip (along the temporal dimension). However, not all parts of a video are equally importa... |
Fadadu_Multi-View_Fusion_of_Sensor_Data_for_Improved_Perception_and_Prediction_WACV_2022_paper | Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving | [
"Sudeep Fadadu",
"Shreyash Pandey",
"Darshan Hegde",
"Yi Shi",
"Fang-Chieh Chou",
"Nemanja Djuric",
"Carlos Vallespi-Gonzalez"
] | https://openaccess.thecvf.com/content/WACV2022/html/Fadadu_Multi-View_Fusion_of_Sensor_Data_for_Improved_Perception_and_Prediction_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Fadadu_Multi-View_Fusion_of_Sensor_Data_for_Improved_Perception_and_Prediction_WACV_2022_paper.pdf | null | 2008.11901 | cvf | @InProceedings{Fadadu_2022_WACV,
author = {Fadadu, Sudeep and Pandey, Shreyash and Hegde, Darshan and Shi, Yi and Chou, Fang-Chieh and Djuric, Nemanja and Vallespi-Gonzalez, Carlos},
title = {Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving},
booktitle = {... | We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized features from a sequence of historical LiDAR data as well as rasterized high-definition map to ... |
Yin_ADC_Adversarial_Attacks_Against_Object_Detection_That_Evade_Context_Consistency_WACV_2022_paper | ADC: Adversarial Attacks Against Object Detection That Evade Context Consistency Checks | [
"Mingjun Yin",
"Shasha Li",
"Chengyu Song",
"M. Salman Asif",
"Amit K. Roy-Chowdhury",
"Srikanth V. Krishnamurthy"
] | https://openaccess.thecvf.com/content/WACV2022/html/Yin_ADC_Adversarial_Attacks_Against_Object_Detection_That_Evade_Context_Consistency_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Yin_ADC_Adversarial_Attacks_Against_Object_Detection_That_Evade_Context_Consistency_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Yin_ADC_Adversarial_Attacks_WACV_2022_supplemental.pdf | 2110.12321 | cvf | @InProceedings{Yin_2022_WACV,
author = {Yin, Mingjun and Li, Shasha and Song, Chengyu and Asif, M. Salman and Roy-Chowdhury, Amit K. and Krishnamurthy, Srikanth V.},
title = {ADC: Adversarial Attacks Against Object Detection That Evade Context Consistency Checks},
booktitle = {Proceedings of the IEEE... | Deep Neural Networks (DNNs) have been shown to be vulnerable to adversarial examples, which are slightly perturbed input images which lead DNNs to make wrong predictions. To protect from such examples, various defense strategies have been proposed. A very recent defense strategy for detecting adversarial examples, that... |
Ho_Deep_Photo_Scan_Semi-Supervised_Learning_for_Dealing_With_the_Real-World_WACV_2022_paper | Deep Photo Scan: Semi-Supervised Learning for Dealing With the Real-World Degradation in Smartphone Photo Scanning | [
"Man M. Ho",
"Jinjia Zhou"
] | https://openaccess.thecvf.com/content/WACV2022/html/Ho_Deep_Photo_Scan_Semi-Supervised_Learning_for_Dealing_With_the_Real-World_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Ho_Deep_Photo_Scan_Semi-Supervised_Learning_for_Dealing_With_the_Real-World_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Ho_Deep_Photo_Scan_WACV_2022_supplemental.pdf | 2102.06120 | cvf | @InProceedings{Ho_2022_WACV,
author = {Ho, Man M. and Zhou, Jinjia},
title = {Deep Photo Scan: Semi-Supervised Learning for Dealing With the Real-World Degradation in Smartphone Photo Scanning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Physical photographs now can be conveniently scanned by smartphones and stored forever as digital images, yet the scanned photos are not restored well. One solution is to train a supervised deep neural network on many digital images and their smartphone-scanned versions. However, it requires a high labor cost, leading ... |
Lee_Contextual_Gradient_Scaling_for_Few-Shot_Learning_WACV_2022_paper | Contextual Gradient Scaling for Few-Shot Learning | [
"Sanghyuk Lee",
"Seunghyun Lee",
"Byung Cheol Song"
] | https://openaccess.thecvf.com/content/WACV2022/html/Lee_Contextual_Gradient_Scaling_for_Few-Shot_Learning_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Lee_Contextual_Gradient_Scaling_for_Few-Shot_Learning_WACV_2022_paper.pdf | https://openaccess.thecvf.com/content/WACV2022/supplemental/Lee_Contextual_Gradient_Scaling_WACV_2022_supplemental.pdf | 2110.10353 | cvf | @InProceedings{Lee_2022_WACV,
author = {Lee, Sanghyuk and Lee, Seunghyun and Song, Byung Cheol},
title = {Contextual Gradient Scaling for Few-Shot Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Model-agnostic meta-learning (MAML) is a well-known optimization-based meta-learning algorithm that works well in various computer vision tasks, e.g., few-shot classification. MAML is to learn an initialization so that a model can adapt to a new task in a few steps. However, since the gradient norm of a classifier (hea... |
Chen_MM-ViT_Multi-Modal_Video_Transformer_for_Compressed_Video_Action_Recognition_WACV_2022_paper | MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition | [
"Jiawei Chen",
"Chiu Man Ho"
] | https://openaccess.thecvf.com/content/WACV2022/html/Chen_MM-ViT_Multi-Modal_Video_Transformer_for_Compressed_Video_Action_Recognition_WACV_2022_paper.html | https://openaccess.thecvf.com/content/WACV2022/papers/Chen_MM-ViT_Multi-Modal_Video_Transformer_for_Compressed_Video_Action_Recognition_WACV_2022_paper.pdf | null | 2108.09322 | title_snapshot | @InProceedings{Chen_2022_WACV,
author = {Chen, Jiawei and Ho, Chiu Man},
title = {MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | This paper presents a pure transformer-based approach, dubbed the Multi-Modal Video Transformer (MM-ViT), for video action recognition. Different from other schemes which solely utilize the decoded RGB frames, MM-ViT operates exclusively in the compressed video domain and exploits all readily available modalities, i.e.... |
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