paper_id stringlengths 44 122 | title stringlengths 22 143 | authors listlengths 1 13 | cvf_url stringlengths 101 179 | pdf_url stringlengths 102 180 | supp_url stringlengths 102 143 ⌀ | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 3
values | bibtex large_stringlengths 315 613 | abstract large_stringlengths 593 1.96k |
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Chawla_Data-Free_Knowledge_Distillation_for_Object_Detection_WACV_2021_paper | Data-Free Knowledge Distillation for Object Detection | [
"Akshay Chawla",
"Hongxu Yin",
"Pavlo Molchanov",
"Jose Alvarez"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chawla_Data-Free_Knowledge_Distillation_for_Object_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chawla_Data-Free_Knowledge_Distillation_for_Object_Detection_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Chawla_Data-Free_Knowledge_Distillation_WACV_2021_supplemental.pdf | null | null | @InProceedings{Chawla_2021_WACV,
author = {Chawla, Akshay and Yin, Hongxu and Molchanov, Pavlo and Alvarez, Jose},
title = {Data-Free Knowledge Distillation for Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {J... | We present DeepInversion for Object Detection (DIODE) to enable data-free knowledge distillation for neural networks trained on the object detection task. From a data-free perspective, DIODE synthesizes images given only an off-the-shelf pre-trained detection network and without any prior domain knowledge, generator ne... |
Miller_Class_Anchor_Clustering_A_Loss_for_Distance-Based_Open_Set_Recognition_WACV_2021_paper | Class Anchor Clustering: A Loss for Distance-Based Open Set Recognition | [
"Dimity Miller",
"Niko Sunderhauf",
"Michael Milford",
"Feras Dayoub"
] | https://openaccess.thecvf.com/content/WACV2021/html/Miller_Class_Anchor_Clustering_A_Loss_for_Distance-Based_Open_Set_Recognition_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Miller_Class_Anchor_Clustering_A_Loss_for_Distance-Based_Open_Set_Recognition_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Miller_Class_Anchor_Clustering_WACV_2021_supplemental.pdf | 2004.02434 | title_snapshot | @InProceedings{Miller_2021_WACV,
author = {Miller, Dimity and Sunderhauf, Niko and Milford, Michael and Dayoub, Feras},
title = {Class Anchor Clustering: A Loss for Distance-Based Open Set Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WAC... | In open set recognition, deep neural networks encounter object classes that were unknown during training. Existing open set classifiers distinguish between known and unknown classes by measuring distance in a network's logit space, assuming that known classes cluster closer to the training data than unknown classes. Ho... |
Belharbi_Deep_Active_Learning_for_Joint_Classification__Segmentation_With_Weak_WACV_2021_paper | Deep Active Learning for Joint Classification & Segmentation With Weak Annotator | [
"Soufiane Belharbi",
"Ismail Ben Ayed",
"Luke McCaffrey",
"Eric Granger"
] | https://openaccess.thecvf.com/content/WACV2021/html/Belharbi_Deep_Active_Learning_for_Joint_Classification__Segmentation_With_Weak_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Belharbi_Deep_Active_Learning_for_Joint_Classification__Segmentation_With_Weak_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Belharbi_Deep_Active_Learning_WACV_2021_supplemental.pdf | 2010.04889 | cvf | @InProceedings{Belharbi_2021_WACV,
author = {Belharbi, Soufiane and Ben Ayed, Ismail and McCaffrey, Luke and Granger, Eric},
title = {Deep Active Learning for Joint Classification \& Segmentation With Weak Annotator},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compu... | CNN visualization and interpretation methods, like class-activation maps (CAMs), are typically used to highlight the image regions linked to class predictions. These models allow to simultaneously classify images and extract class-dependent saliency maps, without the need for costly pixel-level annotations. However, th... |
Lionar_Dynamic_Plane_Convolutional_Occupancy_Networks_WACV_2021_paper | Dynamic Plane Convolutional Occupancy Networks | [
"Stefan Lionar",
"Daniil Emtsev",
"Dusan Svilarkovic",
"Songyou Peng"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lionar_Dynamic_Plane_Convolutional_Occupancy_Networks_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lionar_Dynamic_Plane_Convolutional_Occupancy_Networks_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Lionar_Dynamic_Plane_Convolutional_WACV_2021_supplemental.pdf | 2011.05813 | cvf | @InProceedings{Lionar_2021_WACV,
author = {Lionar, Stefan and Emtsev, Daniil and Svilarkovic, Dusan and Peng, Songyou},
title = {Dynamic Plane Convolutional Occupancy Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Jan... | Learning-based 3D reconstruction using implicit neural representations has shown promising progress not only at the object level but also in more complicated scenes. In this paper, we propose Dynamic Plane Convolutional Occupancy Networks, a novel implicit representation pushing further the quality of 3D surface recons... |
Wu_Fine-Grained_Foreground_Retrieval_via_Teacher-Student_Learning_WACV_2021_paper | Fine-Grained Foreground Retrieval via Teacher-Student Learning | [
"Zongze Wu",
"Dani Lischinski",
"Eli Shechtman"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wu_Fine-Grained_Foreground_Retrieval_via_Teacher-Student_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wu_Fine-Grained_Foreground_Retrieval_via_Teacher-Student_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Wu_Fine-Grained_Foreground_Retrieval_WACV_2021_supplemental.zip | null | null | @InProceedings{Wu_2021_WACV,
author = {Wu, Zongze and Lischinski, Dani and Shechtman, Eli},
title = {Fine-Grained Foreground Retrieval via Teacher-Student Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
y... | Foreground image retrieval is a fundamental task in computer vision. Given an image of the background scene with a bounding box indicating the target location, the goal is to retrieve a set of images of foreground objects from a given category, which are semantically compatible with the background. We formulate foregro... |
Liu_Unsupervised_Multimodal_Video-to-Video_Translation_via_Self-Supervised_Learning_WACV_2021_paper | Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning | [
"Kangning Liu",
"Shuhang Gu",
"Andres Romero",
"Radu Timofte"
] | https://openaccess.thecvf.com/content/WACV2021/html/Liu_Unsupervised_Multimodal_Video-to-Video_Translation_via_Self-Supervised_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Liu_Unsupervised_Multimodal_Video-to-Video_Translation_via_Self-Supervised_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Liu_Unsupervised_Multimodal_Video-to-Video_WACV_2021_supplemental.zip | 2004.06502 | cvf | @InProceedings{Liu_2021_WACV,
author = {Liu, Kangning and Gu, Shuhang and Romero, Andres and Timofte, Radu},
title = {Unsupervised Multimodal Video-to-Video Translation via Self-Supervised Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}... | Existing unsupervised video-to-video translation methods fail to produce translated videos which are frame-wise realistic, semantic information preserving and video-level consistent. In this work, we propose a novel unsupervised video-to-video translation model. Our model decomposes the style and the content uses the s... |
Rymarczyk_Kernel_Self-Attention_for_Weakly-Supervised_Image_Classification_Using_Deep_Multiple_Instance_WACV_2021_paper | Kernel Self-Attention for Weakly-Supervised Image Classification Using Deep Multiple Instance Learning | [
"Dawid Rymarczyk",
"Adriana Borowa",
"Jacek Tabor",
"Bartosz Zielinski"
] | https://openaccess.thecvf.com/content/WACV2021/html/Rymarczyk_Kernel_Self-Attention_for_Weakly-Supervised_Image_Classification_Using_Deep_Multiple_Instance_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Rymarczyk_Kernel_Self-Attention_for_Weakly-Supervised_Image_Classification_Using_Deep_Multiple_Instance_WACV_2021_paper.pdf | null | 2005.12991 | title_judge | @InProceedings{Rymarczyk_2021_WACV,
author = {Rymarczyk, Dawid and Borowa, Adriana and Tabor, Jacek and Zielinski, Bartosz},
title = {Kernel Self-Attention for Weakly-Supervised Image Classification Using Deep Multiple Instance Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on ... | Not all supervised learning problems are described by a pair of a fixed-size input tensor and a label. In some cases, especially in medical image analysis, a label corresponds to a bag of instances (e.g. image patches), and to classify such bag, aggregation of information from all of the instances is needed. There have... |
Xu_Real-Time_Gait-Based_Age_Estimation_and_Gender_Classification_From_a_Single_WACV_2021_paper | Real-Time Gait-Based Age Estimation and Gender Classification From a Single Image | [
"Chi Xu",
"Yasushi Makihara",
"Ruochen Liao",
"Hirotaka Niitsuma",
"Xiang Li",
"Yasushi Yagi",
"Jianfeng Lu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Xu_Real-Time_Gait-Based_Age_Estimation_and_Gender_Classification_From_a_Single_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Xu_Real-Time_Gait-Based_Age_Estimation_and_Gender_Classification_From_a_Single_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Xu_Real-Time_Gait-Based_Age_WACV_2021_supplemental.zip | null | null | @InProceedings{Xu_2021_WACV,
author = {Xu, Chi and Makihara, Yasushi and Liao, Ruochen and Niitsuma, Hirotaka and Li, Xiang and Yagi, Yasushi and Lu, Jianfeng},
title = {Real-Time Gait-Based Age Estimation and Gender Classification From a Single Image},
booktitle = {Proceedings of the IEEE/CVF Winter... | In this paper, we propose a unified real-time framework for gait-based age estimation and gender classification that uses just a single image, which reduces the latency in video capturing compared with the existing methods based on a gait cycle. To cope with the problem of lacking motion information in the input single... |
Anirudh_Generative_Patch_Priors_for_Practical_Compressive_Image_Recovery_WACV_2021_paper | Generative Patch Priors for Practical Compressive Image Recovery | [
"Rushil Anirudh",
"Suhas Lohit",
"Pavan Turaga"
] | https://openaccess.thecvf.com/content/WACV2021/html/Anirudh_Generative_Patch_Priors_for_Practical_Compressive_Image_Recovery_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Anirudh_Generative_Patch_Priors_for_Practical_Compressive_Image_Recovery_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Anirudh_Generative_Patch_Priors_WACV_2021_supplemental.pdf | 2006.10873 | cvf | @InProceedings{Anirudh_2021_WACV,
author = {Anirudh, Rushil and Lohit, Suhas and Turaga, Pavan},
title = {Generative Patch Priors for Practical Compressive Image Recovery},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January}... | In this paper, we propose the generative patch prior (GPP) that defines a generative prior for compressive image recovery, based on patch-manifold models. Unlike learned, image-level priors that are restricted to the range space of a pre-trained generator, GPP can recover a wide variety of natural images using a pre-tr... |
Rotsidis_ExMaps_Long-Term_Localization_in_Dynamic_Scenes_Using_Exponential_Decay_WACV_2021_paper | ExMaps: Long-Term Localization in Dynamic Scenes Using Exponential Decay | [
"Alexandros Rotsidis",
"Christof Lutteroth",
"Peter Hall",
"Christian Richardt"
] | https://openaccess.thecvf.com/content/WACV2021/html/Rotsidis_ExMaps_Long-Term_Localization_in_Dynamic_Scenes_Using_Exponential_Decay_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Rotsidis_ExMaps_Long-Term_Localization_in_Dynamic_Scenes_Using_Exponential_Decay_WACV_2021_paper.pdf | null | null | null | @InProceedings{Rotsidis_2021_WACV,
author = {Rotsidis, Alexandros and Lutteroth, Christof and Hall, Peter and Richardt, Christian},
title = {ExMaps: Long-Term Localization in Dynamic Scenes Using Exponential Decay},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compute... | Visual camera localization using offline maps is widespread in robotics and mobile applications. Most state-of-the-art localization approaches assume static scenes, so maps are often reconstructed once and then kept constant. However, many scenes are dynamic and as changes in the scene happen, future localization attem... |
Tripathy_FACEGAN_Facial_Attribute_Controllable_rEenactment_GAN_WACV_2021_paper | FACEGAN: Facial Attribute Controllable rEenactment GAN | [
"Soumya Tripathy",
"Juho Kannala",
"Esa Rahtu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tripathy_FACEGAN_Facial_Attribute_Controllable_rEenactment_GAN_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tripathy_FACEGAN_Facial_Attribute_Controllable_rEenactment_GAN_WACV_2021_paper.pdf | null | 2011.04439 | cvf | @InProceedings{Tripathy_2021_WACV,
author = {Tripathy, Soumya and Kannala, Juho and Rahtu, Esa},
title = {FACEGAN: Facial Attribute Controllable rEenactment GAN},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year... | The face reenactment is a popular facial animation method where the person's identity is taken from the source image and the facial motion from the driving image. Recent works have demonstrated high-quality results by combin- ing the facial landmark-based motion representations with the generative adversarial networks.... |
Gong_Effective_Fusion_Factor_in_FPN_for_Tiny_Object_Detection_WACV_2021_paper | Effective Fusion Factor in FPN for Tiny Object Detection | [
"Yuqi Gong",
"Xuehui Yu",
"Yao Ding",
"Xiaoke Peng",
"Jian Zhao",
"Zhenjun Han"
] | https://openaccess.thecvf.com/content/WACV2021/html/Gong_Effective_Fusion_Factor_in_FPN_for_Tiny_Object_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Gong_Effective_Fusion_Factor_in_FPN_for_Tiny_Object_Detection_WACV_2021_paper.pdf | null | 2011.02298 | cvf | @InProceedings{Gong_2021_WACV,
author = {Gong, Yuqi and Yu, Xuehui and Ding, Yao and Peng, Xiaoke and Zhao, Jian and Han, Zhenjun},
title = {Effective Fusion Factor in FPN for Tiny Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)}... | FPN-based detectors have made significant progress in general object detection,e.g., MS COCO and CityPersons.However, these detectors fail in certain application scenarios,e.g., tiny object detection. In this paper, we argue that the top-down connections between adjacent layers in FPN bring two-side influences for tiny... |
Liew_Deep_Interactive_Thin_Object_Selection_WACV_2021_paper | Deep Interactive Thin Object Selection | [
"Jun Hao Liew",
"Scott Cohen",
"Brian Price",
"Long Mai",
"Jiashi Feng"
] | https://openaccess.thecvf.com/content/WACV2021/html/Liew_Deep_Interactive_Thin_Object_Selection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Liew_Deep_Interactive_Thin_Object_Selection_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Liew_Deep_Interactive_Thin_WACV_2021_supplemental.pdf | null | null | @InProceedings{Liew_2021_WACV,
author = {Liew, Jun Hao and Cohen, Scott and Price, Brian and Mai, Long and Feng, Jiashi},
title = {Deep Interactive Thin Object Selection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},... | Existing deep learning based interactive segmentation methods have achieved remarkable performance with only a few user clicks, e.g. DEXTR attaining 91.5% IoU on PASCAL VOC with only four extreme clicks. However, we observe even the state-of-the-art methods would often struggle in cases of objects to be segmented with ... |
Shukla_Zero-Pair_Image_to_Image_Translation_Using_Domain_Conditional_Normalization_WACV_2021_paper | Zero-Pair Image to Image Translation Using Domain Conditional Normalization | [
"Samarth Shukla",
"Andres Romero",
"Luc Van Gool",
"Radu Timofte"
] | https://openaccess.thecvf.com/content/WACV2021/html/Shukla_Zero-Pair_Image_to_Image_Translation_Using_Domain_Conditional_Normalization_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Shukla_Zero-Pair_Image_to_Image_Translation_Using_Domain_Conditional_Normalization_WACV_2021_paper.pdf | null | 2011.05680 | cvf | @InProceedings{Shukla_2021_WACV,
author = {Shukla, Samarth and Romero, Andres and Van Gool, Luc and Timofte, Radu},
title = {Zero-Pair Image to Image Translation Using Domain Conditional Normalization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WAC... | In this paper, we propose an approach based on domain conditional normalization (DCN) for zero-pair image-to-image translation, i.e., translating between two domains which have no paired training data available but each have paired training data with a third domain. We employ a single generator which has an encoder-dec... |
Mazumder_RNNP_A_Robust_Few-Shot_Learning_Approach_WACV_2021_paper | RNNP: A Robust Few-Shot Learning Approach | [
"Pratik Mazumder",
"Pravendra Singh",
"Vinay P. Namboodiri"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mazumder_RNNP_A_Robust_Few-Shot_Learning_Approach_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mazumder_RNNP_A_Robust_Few-Shot_Learning_Approach_WACV_2021_paper.pdf | null | 2011.11067 | cvf | @InProceedings{Mazumder_2021_WACV,
author = {Mazumder, Pratik and Singh, Pravendra and Namboodiri, Vinay P.},
title = {RNNP: A Robust Few-Shot Learning Approach},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year... | Learning from a few examples is an important practical aspect of training classifiers. Various works have examined this aspect quite well. However, all existing approaches assume that the few examples provided are always correctly labeled. This is a strong assumption, especially if one considers the current techniques ... |
Lu_An_Alternative_of_LIDAR_in_Nighttime_Unsupervised_Depth_Estimation_Based_WACV_2021_paper | An Alternative of LIDAR in Nighttime: Unsupervised Depth Estimation Based on Single Thermal Image | [
"Yawen Lu",
"Guoyu Lu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lu_An_Alternative_of_LIDAR_in_Nighttime_Unsupervised_Depth_Estimation_Based_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lu_An_Alternative_of_LIDAR_in_Nighttime_Unsupervised_Depth_Estimation_Based_WACV_2021_paper.pdf | null | null | null | @InProceedings{Lu_2021_WACV,
author = {Lu, Yawen and Lu, Guoyu},
title = {An Alternative of LIDAR in Nighttime: Unsupervised Depth Estimation Based on Single Thermal Image},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January... | Most existing autonomous driving vehicles and robots rely on active LIDAR sensors to detect the depth of the surrounding environment, which usually has limited resolution, and the emitted laser can be harmful to people and the environment. Current passive image-based depth estimation algorithms focus on color images fr... |
Yang_Class-Agnostic_Few-Shot_Object_Counting_WACV_2021_paper | Class-Agnostic Few-Shot Object Counting | [
"Shuo-Diao Yang",
"Hung-Ting Su",
"Winston H. Hsu",
"Wen-Chin Chen"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yang_Class-Agnostic_Few-Shot_Object_Counting_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yang_Class-Agnostic_Few-Shot_Object_Counting_WACV_2021_paper.pdf | null | null | null | @InProceedings{Yang_2021_WACV,
author = {Yang, Shuo-Diao and Su, Hung-Ting and Hsu, Winston H. and Chen, Wen-Chin},
title = {Class-Agnostic Few-Shot Object Counting},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
... | Object counting which aims to calculate the number of total instances of the given class is a classic but crucial task that can be applied to many applications. Most of the prior works only focus on counting certain classes of objects such as people, cars, animals, etc. However, in recent years, there are lots of appli... |
Dewil_Self-Supervised_Training_for_Blind_Multi-Frame_Video_Denoising_WACV_2021_paper | Self-Supervised Training for Blind Multi-Frame Video Denoising | [
"Valery Dewil",
"Jeremy Anger",
"Axel Davy",
"Thibaud Ehret",
"Gabriele Facciolo",
"Pablo Arias"
] | https://openaccess.thecvf.com/content/WACV2021/html/Dewil_Self-Supervised_Training_for_Blind_Multi-Frame_Video_Denoising_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Dewil_Self-Supervised_Training_for_Blind_Multi-Frame_Video_Denoising_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Dewil_Self-Supervised_Training_for_WACV_2021_supplemental.pdf | 2004.06957 | cvf | @InProceedings{Dewil_2021_WACV,
author = {Dewil, Valery and Anger, Jeremy and Davy, Axel and Ehret, Thibaud and Facciolo, Gabriele and Arias, Pablo},
title = {Self-Supervised Training for Blind Multi-Frame Video Denoising},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of... | We propose a self-supervised approach for training multi-frame video denoising networks. These networks predict frame t from a window of frames around t. Our self-supervised approach benefits from the video temporal consistency by penalizing a loss between the predicted frame t and a neighboring target frame, which are... |
Mazumder_Improving_Few-Shot_Learning_Using_Composite_Rotation_Based_Auxiliary_Task_WACV_2021_paper | Improving Few-Shot Learning Using Composite Rotation Based Auxiliary Task | [
"Pratik Mazumder",
"Pravendra Singh",
"Vinay P. Namboodiri"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mazumder_Improving_Few-Shot_Learning_Using_Composite_Rotation_Based_Auxiliary_Task_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mazumder_Improving_Few-Shot_Learning_Using_Composite_Rotation_Based_Auxiliary_Task_WACV_2021_paper.pdf | null | 2006.15919 | cvf | @InProceedings{Mazumder_2021_WACV,
author = {Mazumder, Pratik and Singh, Pravendra and Namboodiri, Vinay P.},
title = {Improving Few-Shot Learning Using Composite Rotation Based Auxiliary Task},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | In this paper, we propose an approach to improve few-shot classification performance using a composite rotation based auxiliary task. Few-shot classification methods aim to produce neural networks that perform well for classes with a large number of training samples and classes with less number of training samples. The... |
Jordao_Covariance-Free_Partial_Least_Squares_An_Incremental_Dimensionality_Reduction_Method_WACV_2021_paper | Covariance-Free Partial Least Squares: An Incremental Dimensionality Reduction Method | [
"Artur Jordao",
"Maiko Lie",
"Victor Hugo Cunha de Melo",
"William Robson Schwartz"
] | https://openaccess.thecvf.com/content/WACV2021/html/Jordao_Covariance-Free_Partial_Least_Squares_An_Incremental_Dimensionality_Reduction_Method_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Jordao_Covariance-Free_Partial_Least_Squares_An_Incremental_Dimensionality_Reduction_Method_WACV_2021_paper.pdf | null | 1910.02319 | cvf | @InProceedings{Jordao_2021_WACV,
author = {Jordao, Artur and Lie, Maiko and de Melo, Victor Hugo Cunha and Schwartz, William Robson},
title = {Covariance-Free Partial Least Squares: An Incremental Dimensionality Reduction Method},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicat... | Dimensionality reduction plays an important role in computer vision problems since it reduces computational cost and is often capable of yielding more discriminative data representation. In this context, Partial Least Squares (PLS) has presented notable results in tasks such as image classification and neural network o... |
Behjati_OverNet_Lightweight_Multi-Scale_Super-Resolution_With_Overscaling_Network_WACV_2021_paper | OverNet: Lightweight Multi-Scale Super-Resolution With Overscaling Network | [
"Parichehr Behjati",
"Pau Rodriguez",
"Armin Mehri",
"Isabelle Hupont",
"Carles Fernandez Tena",
"Jordi Gonzalez"
] | https://openaccess.thecvf.com/content/WACV2021/html/Behjati_OverNet_Lightweight_Multi-Scale_Super-Resolution_With_Overscaling_Network_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Behjati_OverNet_Lightweight_Multi-Scale_Super-Resolution_With_Overscaling_Network_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Behjati_OverNet_Lightweight_Multi-Scale_WACV_2021_supplemental.pdf | 2008.02382 | cvf | @InProceedings{Behjati_2021_WACV,
author = {Behjati, Parichehr and Rodriguez, Pau and Mehri, Armin and Hupont, Isabelle and Tena, Carles Fernandez and Gonzalez, Jordi},
title = {OverNet: Lightweight Multi-Scale Super-Resolution With Overscaling Network},
booktitle = {Proceedings of the IEEE/CVF Winte... | Super-resolution (SR) has achieved great success due to the development of deep convolutional neural networks (CNNs). However, as the depth and width of the networks increase, CNN-based SR methods have been faced with the challenge of computational complexity in practice. Moreover, most SR methods train a dedicated mod... |
Xiao_One-Shot_Image_Recognition_Using_Prototypical_Encoders_With_Reduced_Hubness_WACV_2021_paper | One-Shot Image Recognition Using Prototypical Encoders With Reduced Hubness | [
"Chenxi Xiao",
"Naveen Madapana",
"Juan Wachs"
] | https://openaccess.thecvf.com/content/WACV2021/html/Xiao_One-Shot_Image_Recognition_Using_Prototypical_Encoders_With_Reduced_Hubness_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Xiao_One-Shot_Image_Recognition_Using_Prototypical_Encoders_With_Reduced_Hubness_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Xiao_One-Shot_Image_Recognition_WACV_2021_supplemental.pdf | null | null | @InProceedings{Xiao_2021_WACV,
author = {Xiao, Chenxi and Madapana, Naveen and Wachs, Juan},
title = {One-Shot Image Recognition Using Prototypical Encoders With Reduced Hubness},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {J... | Humans have the innate ability to recognize new objects just by looking at sketches of them (also referred as to prototype images). Similarly, prototypical images can be used as an effective visual representations of unseen classes to tackle few-shot learning (FSL) tasks. Our main goal is to recognize unseen hand signs... |
Bashirov_Real-Time_RGBD-Based_Extended_Body_Pose_Estimation_WACV_2021_paper | Real-Time RGBD-Based Extended Body Pose Estimation | [
"Renat Bashirov",
"Anastasia Ianina",
"Karim Iskakov",
"Yevgeniy Kononenko",
"Valeriya Strizhkova",
"Victor Lempitsky",
"Alexander Vakhitov"
] | https://openaccess.thecvf.com/content/WACV2021/html/Bashirov_Real-Time_RGBD-Based_Extended_Body_Pose_Estimation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Bashirov_Real-Time_RGBD-Based_Extended_Body_Pose_Estimation_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Bashirov_Real-Time_RGBD-Based_Extended_WACV_2021_supplemental.zip | 2103.03663 | title_snapshot | @InProceedings{Bashirov_2021_WACV,
author = {Bashirov, Renat and Ianina, Anastasia and Iskakov, Karim and Kononenko, Yevgeniy and Strizhkova, Valeriya and Lempitsky, Victor and Vakhitov, Alexander},
title = {Real-Time RGBD-Based Extended Body Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF... | We present a system for real-time RGBD-based estimation of 3D human pose. We use parametric 3D deformable human mesh model (SMPL-X) as a representation and focus on the real-time estimation of parameters for the body pose, hands pose and facial expression from Kinect Azure RGB-D camera. We train estimators of body pose... |
Kobayashi_Group_Softmax_Loss_With_Discriminative_Feature_Grouping_WACV_2021_paper | Group Softmax Loss With Discriminative Feature Grouping | [
"Takumi Kobayashi"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kobayashi_Group_Softmax_Loss_With_Discriminative_Feature_Grouping_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kobayashi_Group_Softmax_Loss_With_Discriminative_Feature_Grouping_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kobayashi_Group_Softmax_Loss_WACV_2021_supplemental.pdf | null | null | @InProceedings{Kobayashi_2021_WACV,
author = {Kobayashi, Takumi},
title = {Group Softmax Loss With Discriminative Feature Grouping},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pages ... | In the supervised learning framework, a softmax cross-entropy loss is commonly applied to train deep neural networks for high-performance classification. It, however, demands large amount of annotated data and fails to learn the discriminative networks on a smaller amount of data. In this paper, we propose a novel loss... |
Ben-Artzi_Separable_Four_Points_Fundamental_Matrix_WACV_2021_paper | Separable Four Points Fundamental Matrix | [
"Gil Ben-Artzi"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ben-Artzi_Separable_Four_Points_Fundamental_Matrix_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ben-Artzi_Separable_Four_Points_Fundamental_Matrix_WACV_2021_paper.pdf | null | 2006.05926 | title_snapshot | @InProceedings{Ben-Artzi_2021_WACV,
author = {Ben-Artzi, Gil},
title = {Separable Four Points Fundamental Matrix},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pages = {188-196}
} | We present a novel approach for RANSAC-based computation of the fundamental matrix based on epipolar homography decomposition. We analyze the geometrical meaning of the decomposition-based representation and show that it directly induces a consecutive sampling strategy of two independent sets of correspondences. We sho... |
Kawasaki_Multimodal_Trajectory_Predictions_for_Autonomous_Driving_Without_a_Detailed_Prior_WACV_2021_paper | Multimodal Trajectory Predictions for Autonomous Driving Without a Detailed Prior Map | [
"Atsushi Kawasaki",
"Akihito Seki"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kawasaki_Multimodal_Trajectory_Predictions_for_Autonomous_Driving_Without_a_Detailed_Prior_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kawasaki_Multimodal_Trajectory_Predictions_for_Autonomous_Driving_Without_a_Detailed_Prior_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kawasaki_Multimodal_Trajectory_Predictions_WACV_2021_supplemental.pdf | null | null | @InProceedings{Kawasaki_2021_WACV,
author = {Kawasaki, Atsushi and Seki, Akihito},
title = {Multimodal Trajectory Predictions for Autonomous Driving Without a Detailed Prior Map},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {J... | Predicting the future trajectories of surrounding vehicles is a key competence for safe and efficient real-world autonomous driving systems. Previous works have presented deep neural network models for predictions using a detailed prior map which includes driving lanes and explicitly expresses the road rules like legal... |
Wen_Handwritten_Chinese_Font_Generation_With_Collaborative_Stroke_Refinement_WACV_2021_paper | Handwritten Chinese Font Generation With Collaborative Stroke Refinement | [
"Chuan Wen",
"Yujie Pan",
"Jie Chang",
"Ya Zhang",
"Siheng Chen",
"Yanfeng Wang",
"Mei Han",
"Qi Tian"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wen_Handwritten_Chinese_Font_Generation_With_Collaborative_Stroke_Refinement_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wen_Handwritten_Chinese_Font_Generation_With_Collaborative_Stroke_Refinement_WACV_2021_paper.pdf | null | 1904.13268 | title_snapshot | @InProceedings{Wen_2021_WACV,
author = {Wen, Chuan and Pan, Yujie and Chang, Jie and Zhang, Ya and Chen, Siheng and Wang, Yanfeng and Han, Mei and Tian, Qi},
title = {Handwritten Chinese Font Generation With Collaborative Stroke Refinement},
booktitle = {Proceedings of the IEEE/CVF Winter Conference ... | Automatic character generation is an appealing solution for typeface design, especially for Chinese fonts with over 3700 most commonly-used characters. This task is particularly challenging for handwritten characters with thin strokes which are error-prone during deformation. To handle the generation of thin strokes, w... |
Muller-Budack_Ontology-Driven_Event_Type_Classification_in_Images_WACV_2021_paper | Ontology-Driven Event Type Classification in Images | [
"Eric Muller-Budack",
"Matthias Springstein",
"Sherzod Hakimov",
"Kevin Mrutzek",
"Ralph Ewerth"
] | https://openaccess.thecvf.com/content/WACV2021/html/Muller-Budack_Ontology-Driven_Event_Type_Classification_in_Images_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Muller-Budack_Ontology-Driven_Event_Type_Classification_in_Images_WACV_2021_paper.pdf | null | 2011.04714 | title_snapshot | @InProceedings{Muller-Budack_2021_WACV,
author = {Muller-Budack, Eric and Springstein, Matthias and Hakimov, Sherzod and Mrutzek, Kevin and Ewerth, Ralph},
title = {Ontology-Driven Event Type Classification in Images},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comp... | Event classification can add valuable information for semantic search and the increasingly important topic of fact validation in news. So far, only few approaches address image classification for newsworthy event types such as natural disasters, sports events, or elections. Previous work distinguishes only between a li... |
Pahde_Multimodal_Prototypical_Networks_for_Few-Shot_Learning_WACV_2021_paper | Multimodal Prototypical Networks for Few-Shot Learning | [
"Frederik Pahde",
"Mihai Puscas",
"Tassilo Klein",
"Moin Nabi"
] | https://openaccess.thecvf.com/content/WACV2021/html/Pahde_Multimodal_Prototypical_Networks_for_Few-Shot_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Pahde_Multimodal_Prototypical_Networks_for_Few-Shot_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Pahde_Multimodal_Prototypical_Networks_WACV_2021_supplemental.pdf | 2011.08899 | cvf | @InProceedings{Pahde_2021_WACV,
author = {Pahde, Frederik and Puscas, Mihai and Klein, Tassilo and Nabi, Moin},
title = {Multimodal Prototypical Networks for Few-Shot Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Jan... | Although providing exceptional results for many computer vision tasks, state-of-the-art deep learning algorithms catastrophically struggle in low data scenarios. However, if data in additional modalities exist (e.g. text) this can compensate for the lack of data and improve the classification results. To overcome this ... |
Shere_Temporally_Consistent_3D_Human_Pose_Estimation_Using_Dual_360deg_Cameras_WACV_2021_paper | Temporally Consistent 3D Human Pose Estimation Using Dual 360deg Cameras | [
"Matthew Shere",
"Hansung Kim",
"Adrian Hilton"
] | https://openaccess.thecvf.com/content/WACV2021/html/Shere_Temporally_Consistent_3D_Human_Pose_Estimation_Using_Dual_360deg_Cameras_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Shere_Temporally_Consistent_3D_Human_Pose_Estimation_Using_Dual_360deg_Cameras_WACV_2021_paper.pdf | null | null | null | @InProceedings{Shere_2021_WACV,
author = {Shere, Matthew and Kim, Hansung and Hilton, Adrian},
title = {Temporally Consistent 3D Human Pose Estimation Using Dual 360deg Cameras},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Ja... | This paper presents a 3D human pose estimation system that uses a stereo pair of 360deg sensors to capture the complete scene from a single location. The approach combines the advantages of omnidirectional capture, the accuracy of multiple view 3D pose estimation and the portability of monocular acquisition. Joint mono... |
Ben-Shabat_The_IKEA_ASM_Dataset_Understanding_People_Assembling_Furniture_Through_Actions_WACV_2021_paper | The IKEA ASM Dataset: Understanding People Assembling Furniture Through Actions, Objects and Pose | [
"Yizhak Ben-Shabat",
"Xin Yu",
"Fatemeh Saleh",
"Dylan Campbell",
"Cristian Rodriguez-Opazo",
"Hongdong Li",
"Stephen Gould"
] | https://openaccess.thecvf.com/content/WACV2021/html/Ben-Shabat_The_IKEA_ASM_Dataset_Understanding_People_Assembling_Furniture_Through_Actions_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Ben-Shabat_The_IKEA_ASM_Dataset_Understanding_People_Assembling_Furniture_Through_Actions_WACV_2021_paper.pdf | null | 2007.00394 | title_snapshot | @InProceedings{Ben-Shabat_2021_WACV,
author = {Ben-Shabat, Yizhak and Yu, Xin and Saleh, Fatemeh and Campbell, Dylan and Rodriguez-Opazo, Cristian and Li, Hongdong and Gould, Stephen},
title = {The IKEA ASM Dataset: Understanding People Assembling Furniture Through Actions, Objects and Pose},
booktit... | The availability of a large labelled dataset is a key requirement for applying deep learning methods to solve various computer vision tasks. In the context of understanding human activities, existing public datasets, while large in size, are often limited to a single RGB camera and provide only per-frame or per-clip ac... |
Xu_Vid2Int_Detecting_Implicit_Intention_From_Long_Dialog_Videos_WACV_2021_paper | Vid2Int: Detecting Implicit Intention From Long Dialog Videos | [
"Xiaoli Xu",
"Yao Lu",
"Zhiwu Lu",
"Tao Xiang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Xu_Vid2Int_Detecting_Implicit_Intention_From_Long_Dialog_Videos_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Xu_Vid2Int_Detecting_Implicit_Intention_From_Long_Dialog_Videos_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Xu_Vid2Int_Detecting_Implicit_WACV_2021_supplemental.pdf | null | null | @InProceedings{Xu_2021_WACV,
author = {Xu, Xiaoli and Lu, Yao and Lu, Zhiwu and Xiang, Tao},
title = {Vid2Int: Detecting Implicit Intention From Long Dialog Videos},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
y... | Detecting subtle intention such as deception and subtext of a person in a long dialog video, or implicit intention detection (IID), is a challenging problem. The transcript (textual cues) often reveals little, so audio-visual cues including voice tone as well as facial and body behaviour are the main focuses for automa... |
Tinsley_This_Face_Does_Not_Exist..._But_It_Might_Be_Yours_WACV_2021_paper | This Face Does Not Exist... But It Might Be Yours! Identity Leakage in Generative Models | [
"Patrick Tinsley",
"Adam Czajka",
"Patrick Flynn"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tinsley_This_Face_Does_Not_Exist..._But_It_Might_Be_Yours_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tinsley_This_Face_Does_Not_Exist..._But_It_Might_Be_Yours_WACV_2021_paper.pdf | null | 2101.05084 | title_snapshot | @InProceedings{Tinsley_2021_WACV,
author = {Tinsley, Patrick and Czajka, Adam and Flynn, Patrick},
title = {This Face Does Not Exist... But It Might Be Yours! Identity Leakage in Generative Models},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},... | Generative adversarial networks (GANs) are able to generate high resolution photo-realistic images of objects that "do not exist." These synthetic images are rather difficult to detect as fake. However, the manner in which these generative models are trained hints at a potential for information leakage from the supplie... |
Jing_Adversarial_Dual_Distinct_Classifiers_for_Unsupervised_Domain_Adaptation_WACV_2021_paper | Adversarial Dual Distinct Classifiers for Unsupervised Domain Adaptation | [
"Taotao Jing",
"Zhengming Ding"
] | https://openaccess.thecvf.com/content/WACV2021/html/Jing_Adversarial_Dual_Distinct_Classifiers_for_Unsupervised_Domain_Adaptation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Jing_Adversarial_Dual_Distinct_Classifiers_for_Unsupervised_Domain_Adaptation_WACV_2021_paper.pdf | null | 2008.11878 | cvf | @InProceedings{Jing_2021_WACV,
author = {Jing, Taotao and Ding, Zhengming},
title = {Adversarial Dual Distinct Classifiers for Unsupervised Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Unsupervised Domain adaptation (UDA) attempts to recognize the unlabeled target samples by building a learning model from a differently-distributed labeled source domain. Conventional UDA concentrates on extracting domain-invariant features through deep adversarial networks. However, most of them seek to match the diff... |
Unal_Improving_Point_Cloud_Semantic_Segmentation_by_Learning_3D_Object_Detection_WACV_2021_paper | Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection | [
"Ozan Unal",
"Luc Van Gool",
"Dengxin Dai"
] | https://openaccess.thecvf.com/content/WACV2021/html/Unal_Improving_Point_Cloud_Semantic_Segmentation_by_Learning_3D_Object_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Unal_Improving_Point_Cloud_Semantic_Segmentation_by_Learning_3D_Object_Detection_WACV_2021_paper.pdf | null | 2009.10569 | cvf | @InProceedings{Unal_2021_WACV,
author = {Unal, Ozan and Van Gool, Luc and Dai, Dengxin},
title = {Improving Point Cloud Semantic Segmentation by Learning 3D Object Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {Janua... | Point cloud semantic segmentation plays an essential role in autonomous driving, providing vital information about drivable surfaces and nearby objects that can aid higher level tasks such as path planning and collision avoidance. While current 3D semantic segmentation networks focus on convolutional architectures that... |
Moghaddam_Optimistic_Agent_Accurate_Graph-Based_Value_Estimation_for_More_Successful_Visual_WACV_2021_paper | Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation | [
"Mahdi Kazemi Moghaddam",
"Qi Wu",
"Ehsan Abbasnejad",
"Javen Shi"
] | https://openaccess.thecvf.com/content/WACV2021/html/Moghaddam_Optimistic_Agent_Accurate_Graph-Based_Value_Estimation_for_More_Successful_Visual_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Moghaddam_Optimistic_Agent_Accurate_Graph-Based_Value_Estimation_for_More_Successful_Visual_WACV_2021_paper.pdf | null | 2004.03222 | cvf | @InProceedings{Moghaddam_2021_WACV,
author = {Moghaddam, Mahdi Kazemi and Wu, Qi and Abbasnejad, Ehsan and Shi, Javen},
title = {Optimistic Agent: Accurate Graph-Based Value Estimation for More Successful Visual Navigation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications o... | We humans can impeccably search for a target object, given its name only, even in an unseen environment. We argue this ability is largely due to three main reasons: the incorporation of prior knowledge (or experience), the adaptation of it to the new environment using the observed visual cues and most importantly optim... |
Lee_Local_to_Global_Efficient_Visual_Localization_for_a_Monocular_Camera_WACV_2021_paper | Local to Global: Efficient Visual Localization for a Monocular Camera | [
"Sang Jun Lee",
"Deokhwa Kim",
"Sung Soo Hwang",
"Donghwan Lee"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lee_Local_to_Global_Efficient_Visual_Localization_for_a_Monocular_Camera_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lee_Local_to_Global_Efficient_Visual_Localization_for_a_Monocular_Camera_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Lee_Local_to_Global_WACV_2021_supplemental.zip | null | null | @InProceedings{Lee_2021_WACV,
author = {Lee, Sang Jun and Kim, Deokhwa and Hwang, Sung Soo and Lee, Donghwan},
title = {Local to Global: Efficient Visual Localization for a Monocular Camera},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mo... | Robust and accurate visual localization is one of the most fundamental elements in various technologies, such as autonomous driving and augmented reality. While recent visual localization algorithms demonstrate promising results in terms of accuracy and robustness, the associated high computational cost requires runnin... |
Kayatani_The_Laughing_Machine_Predicting_Humor_in_Video_WACV_2021_paper | The Laughing Machine: Predicting Humor in Video | [
"Yuta Kayatani",
"Zekun Yang",
"Mayu Otani",
"Noa Garcia",
"Chenhui Chu",
"Yuta Nakashima",
"Haruo Takemura"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kayatani_The_Laughing_Machine_Predicting_Humor_in_Video_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kayatani_The_Laughing_Machine_Predicting_Humor_in_Video_WACV_2021_paper.pdf | null | null | null | @InProceedings{Kayatani_2021_WACV,
author = {Kayatani, Yuta and Yang, Zekun and Otani, Mayu and Garcia, Noa and Chu, Chenhui and Nakashima, Yuta and Takemura, Haruo},
title = {The Laughing Machine: Predicting Humor in Video},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications ... | Humor is a very important communication tool; yet, it is an open problem for machines to understand humor. In this paper, we build a new multimodal dataset for humor prediction that includes subtitles and video frames, as well as humor labels associated with video's timestamps. On top of it, we present a model to predi... |
Vascon_Transductive_Visual_Verb_Sense_Disambiguation_WACV_2021_paper | Transductive Visual Verb Sense Disambiguation | [
"Sebastiano Vascon",
"Sinem Aslan",
"Gianluca Bigaglia",
"Lorenzo Giudice",
"Marcello Pelillo"
] | https://openaccess.thecvf.com/content/WACV2021/html/Vascon_Transductive_Visual_Verb_Sense_Disambiguation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Vascon_Transductive_Visual_Verb_Sense_Disambiguation_WACV_2021_paper.pdf | null | 2012.10821 | cvf | @InProceedings{Vascon_2021_WACV,
author = {Vascon, Sebastiano and Aslan, Sinem and Bigaglia, Gianluca and Giudice, Lorenzo and Pelillo, Marcello},
title = {Transductive Visual Verb Sense Disambiguation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WA... | Verb Sense Disambiguation is a well-known task in NLP, the aim is to find the correct sense of a verb in a sentence. Recently, this problem has been extended in a multimodal scenario, by exploiting both textual and visual features of ambiguous verbs leading to a new problem, the Visual Verb Sense Disambiguation (VVSD).... |
Groenendijk_Multi-Loss_Weighting_With_Coefficient_of_Variations_WACV_2021_paper | Multi-Loss Weighting With Coefficient of Variations | [
"Rick Groenendijk",
"Sezer Karaoglu",
"Theo Gevers",
"Thomas Mensink"
] | https://openaccess.thecvf.com/content/WACV2021/html/Groenendijk_Multi-Loss_Weighting_With_Coefficient_of_Variations_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Groenendijk_Multi-Loss_Weighting_With_Coefficient_of_Variations_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Groenendijk_Multi-Loss_Weighting_With_WACV_2021_supplemental.pdf | 2009.01717 | cvf | @InProceedings{Groenendijk_2021_WACV,
author = {Groenendijk, Rick and Karaoglu, Sezer and Gevers, Theo and Mensink, Thomas},
title = {Multi-Loss Weighting With Coefficient of Variations},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Many interesting tasks in machine learning and computer vision are learned by optimising an objective function defined as a weighted linear combination of multiple losses. The final performance is sensitive to choosing the correct (relative) weights for these losses. Finding a good set of weights is often done by adopt... |
Kim_De-Biasing_Neural_Networks_With_Estimated_Offset_for_Class_Imbalanced_Learning_WACV_2021_paper | De-Biasing Neural Networks With Estimated Offset for Class Imbalanced Learning | [
"Byungju Kim",
"Hyeong Gwon Hong",
"Junmo Kim"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kim_De-Biasing_Neural_Networks_With_Estimated_Offset_for_Class_Imbalanced_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kim_De-Biasing_Neural_Networks_With_Estimated_Offset_for_Class_Imbalanced_Learning_WACV_2021_paper.pdf | null | null | null | @InProceedings{Kim_2021_WACV,
author = {Kim, Byungju and Hong, Hyeong Gwon and Kim, Junmo},
title = {De-Biasing Neural Networks With Estimated Offset for Class Imbalanced Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = ... | The imbalanced distribution of the training data makes the networks biased to the frequent classes. Existing methods to resolve the problem involve re-sampling, re-weighting, or cost-sensitive learning. Most of them anticipate that emphasizing the minority classes during the training would help the network to learn bet... |
Yi_Oriented_Object_Detection_in_Aerial_Images_With_Box_Boundary-Aware_Vectors_WACV_2021_paper | Oriented Object Detection in Aerial Images With Box Boundary-Aware Vectors | [
"Jingru Yi",
"Pengxiang Wu",
"Bo Liu",
"Qiaoying Huang",
"Hui Qu",
"Dimitris Metaxas"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yi_Oriented_Object_Detection_in_Aerial_Images_With_Box_Boundary-Aware_Vectors_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yi_Oriented_Object_Detection_in_Aerial_Images_With_Box_Boundary-Aware_Vectors_WACV_2021_paper.pdf | null | 2008.07043 | cvf | @InProceedings{Yi_2021_WACV,
author = {Yi, Jingru and Wu, Pengxiang and Liu, Bo and Huang, Qiaoying and Qu, Hui and Metaxas, Dimitris},
title = {Oriented Object Detection in Aerial Images With Box Boundary-Aware Vectors},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of C... | Oriented object detection in aerial images is a challenging task as the objects in aerial images are displayed in arbitrary directions and are usually densely packed. Current oriented object detection methods mainly rely on two-stage anchor-based detectors. However, the anchor-based detectors typically suffer from a se... |
Yang_IncreACO_Incrementally_Learned_Automatic_Check-Out_With_Photorealistic_Exemplar_Augmentation_WACV_2021_paper | IncreACO: Incrementally Learned Automatic Check-Out With Photorealistic Exemplar Augmentation | [
"Yandan Yang",
"Lu Sheng",
"Xiaolong Jiang",
"Haochen Wang",
"Dong Xu",
"Xianbin Cao"
] | https://openaccess.thecvf.com/content/WACV2021/html/Yang_IncreACO_Incrementally_Learned_Automatic_Check-Out_With_Photorealistic_Exemplar_Augmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Yang_IncreACO_Incrementally_Learned_Automatic_Check-Out_With_Photorealistic_Exemplar_Augmentation_WACV_2021_paper.pdf | null | null | null | @InProceedings{Yang_2021_WACV,
author = {Yang, Yandan and Sheng, Lu and Jiang, Xiaolong and Wang, Haochen and Xu, Dong and Cao, Xianbin},
title = {IncreACO: Incrementally Learned Automatic Check-Out With Photorealistic Exemplar Augmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference... | Automatic check-out (ACO) emerges as an integral component in recent self-service retailing stores, which aims at automatically detecting and counting the randomly placed products upon a check-out platform. Existing data-driven counting works still have difficulties in generalizing to real-world retail product counting... |
Modolo_Understanding_the_Impact_of_Mistakes_on_Background_Regions_in_Crowd_WACV_2021_paper | Understanding the Impact of Mistakes on Background Regions in Crowd Counting | [
"Davide Modolo",
"Bing Shuai",
"Rahul Rama Varior",
"Joseph Tighe"
] | https://openaccess.thecvf.com/content/WACV2021/html/Modolo_Understanding_the_Impact_of_Mistakes_on_Background_Regions_in_Crowd_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Modolo_Understanding_the_Impact_of_Mistakes_on_Background_Regions_in_Crowd_WACV_2021_paper.pdf | null | 2003.13759 | cvf | @InProceedings{Modolo_2021_WACV,
author = {Modolo, Davide and Shuai, Bing and Varior, Rahul Rama and Tighe, Joseph},
title = {Understanding the Impact of Mistakes on Background Regions in Crowd Counting},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | In crowd counting we often observe wrong predictions on image regions not containing any person. But how often do these mistakes happen and how much do they affect the overall performance? In this paper we analyze this problem in depth and present an extensive analysis on five of the most important crowd counting datas... |
Chen_Temporal-Aware_Self-Supervised_Learning_for_3D_Hand_Pose_and_Mesh_Estimation_WACV_2021_paper | Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos | [
"Liangjian Chen",
"Shih-Yao Lin",
"Yusheng Xie",
"Yen-Yu Lin",
"Xiaohui Xie"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chen_Temporal-Aware_Self-Supervised_Learning_for_3D_Hand_Pose_and_Mesh_Estimation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chen_Temporal-Aware_Self-Supervised_Learning_for_3D_Hand_Pose_and_Mesh_Estimation_WACV_2021_paper.pdf | null | 2012.03205 | cvf | @InProceedings{Chen_2021_WACV,
author = {Chen, Liangjian and Lin, Shih-Yao and Xie, Yusheng and Lin, Yen-Yu and Xie, Xiaohui},
title = {Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications o... | Estimating 3D hand pose directly from RGB images is challenging but has gained steady progress recently by training deep models with annotated 3D poses. However annotating 3D poses is difficult and as such only a few 3D hand pose datasets are available, all with limited sample sizes. In this study, we propose a new fra... |
Zhang_Saliency_Prediction_With_External_Knowledge_WACV_2021_paper | Saliency Prediction With External Knowledge | [
"Yifeng Zhang",
"Ming Jiang",
"Qi Zhao"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Saliency_Prediction_With_External_Knowledge_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Saliency_Prediction_With_External_Knowledge_WACV_2021_paper.pdf | null | 2007.13839 | cvf | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Yifeng and Jiang, Ming and Zhao, Qi},
title = {Saliency Prediction With External Knowledge},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
p... | The last decades have seen great progress in saliency prediction, with the success of deep neural networks that are able to encode high-level semantics. Yet, while humans have the innate capability in leveraging their knowledge to decide where to look (e.g. people pay more attention to familiar faces such as celebritie... |
Sandru_SuPEr-SAM_Using_the_Supervision_Signal_From_a_Pose_Estimator_to_WACV_2021_paper | SuPEr-SAM: Using the Supervision Signal From a Pose Estimator to Train a Spatial Attention Module for Personal Protective Equipment Recognition | [
"Adrian Sandru",
"Georgian-Emilian Duta",
"Mariana-Iuliana Georgescu",
"Radu Tudor Ionescu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Sandru_SuPEr-SAM_Using_the_Supervision_Signal_From_a_Pose_Estimator_to_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Sandru_SuPEr-SAM_Using_the_Supervision_Signal_From_a_Pose_Estimator_to_WACV_2021_paper.pdf | null | 2009.12339 | title_snapshot | @InProceedings{Sandru_2021_WACV,
author = {Sandru, Adrian and Duta, Georgian-Emilian and Georgescu, Mariana-Iuliana and Ionescu, Radu Tudor},
title = {SuPEr-SAM: Using the Supervision Signal From a Pose Estimator to Train a Spatial Attention Module for Personal Protective Equipment Recognition},
book... | We propose a deep learning method to automatically detect personal protective equipment (PPE), such as helmets, surgical masks, reflective vests, boots and so on, in images of people. Typical approaches for PPE detection based on deep learning are (i) to train an object detector for items such as those listed above or ... |
Shedligeri_A_Unified_Framework_for_Compressive_Video_Recovery_From_Coded_Exposure_WACV_2021_paper | A Unified Framework for Compressive Video Recovery From Coded Exposure Techniques | [
"Prasan Shedligeri",
"Anupama S",
"Kaushik Mitra"
] | https://openaccess.thecvf.com/content/WACV2021/html/Shedligeri_A_Unified_Framework_for_Compressive_Video_Recovery_From_Coded_Exposure_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Shedligeri_A_Unified_Framework_for_Compressive_Video_Recovery_From_Coded_Exposure_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Shedligeri_A_Unified_Framework_WACV_2021_supplemental.zip | 2011.05532 | cvf | @InProceedings{Shedligeri_2021_WACV,
author = {Shedligeri, Prasan and S, Anupama and Mitra, Kaushik},
title = {A Unified Framework for Compressive Video Recovery From Coded Exposure Techniques},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
... | Several coded exposure techniques have been proposed for acquiring high frame rate videos at low bandwidth. Most recently, a Coded-2-Bucket camera has been proposed that can acquire two compressed measurements in a single exposure, unlike previously proposed coded exposure techniques, which can acquire only a single me... |
Li_Deep_Unsupervised_Anomaly_Detection_WACV_2021_paper | Deep Unsupervised Anomaly Detection | [
"Tangqing Li",
"Zheng Wang",
"Siying Liu",
"Wen-Yan Lin"
] | https://openaccess.thecvf.com/content/WACV2021/html/Li_Deep_Unsupervised_Anomaly_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Li_Deep_Unsupervised_Anomaly_Detection_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Li_Deep_Unsupervised_Anomaly_WACV_2021_supplemental.pdf | null | null | @InProceedings{Li_2021_WACV,
author = {Li, Tangqing and Wang, Zheng and Liu, Siying and Lin, Wen-Yan},
title = {Deep Unsupervised Anomaly Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021... | This paper proposes a novel method to detect anomalies in large datasets under a fully unsupervised setting. The key idea behind our algorithm is to learn the representation underlying normal data. To this end, we leverage the latest clustering technique suitable for handling high dimensional data. This hypothesis prov... |
Bi_Disentangled_Contour_Learning_for_Quadrilateral_Text_Detection_WACV_2021_paper | Disentangled Contour Learning for Quadrilateral Text Detection | [
"Yanguang Bi",
"Zhiqiang Hu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Bi_Disentangled_Contour_Learning_for_Quadrilateral_Text_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Bi_Disentangled_Contour_Learning_for_Quadrilateral_Text_Detection_WACV_2021_paper.pdf | null | null | null | @InProceedings{Bi_2021_WACV,
author = {Bi, Yanguang and Hu, Zhiqiang},
title = {Disentangled Contour Learning for Quadrilateral Text Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
... | Precise detection of quadrilateral text is of great significance for subsequent recognition, where the main challenge comes from four distorted sides. Existing methods concentrate on learning four vertices to construct the contour. However, vertices are dummy intersections entangled by their neighbor sides. The regress... |
Lee_DynaVSR_Dynamic_Adaptive_Blind_Video_Super-Resolution_WACV_2021_paper | DynaVSR: Dynamic Adaptive Blind Video Super-Resolution | [
"Suyoung Lee",
"Myungsub Choi",
"Kyoung Mu Lee"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lee_DynaVSR_Dynamic_Adaptive_Blind_Video_Super-Resolution_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lee_DynaVSR_Dynamic_Adaptive_Blind_Video_Super-Resolution_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Lee_DynaVSR_Dynamic_Adaptive_WACV_2021_supplemental.zip | 2011.04482 | cvf | @InProceedings{Lee_2021_WACV,
author = {Lee, Suyoung and Choi, Myungsub and Lee, Kyoung Mu},
title = {DynaVSR: Dynamic Adaptive Blind Video Super-Resolution},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Most conventional supervised super-resolution (SR) algorithms assume that low-resolution (LR) data is obtained by downscaling high-resolution (HR) data with a fixed known kernel, but such an assumption often does not hold in real scenarios. Some recent blind SR algorithms have been proposed to estimate different downsc... |
Corona_MEVA_A_Large-Scale_Multiview_Multimodal_Video_Dataset_for_Activity_Detection_WACV_2021_paper | MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection | [
"Kellie Corona",
"Katie Osterdahl",
"Roderic Collins",
"Anthony Hoogs"
] | https://openaccess.thecvf.com/content/WACV2021/html/Corona_MEVA_A_Large-Scale_Multiview_Multimodal_Video_Dataset_for_Activity_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Corona_MEVA_A_Large-Scale_Multiview_Multimodal_Video_Dataset_for_Activity_Detection_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Corona_MEVA_A_Large-Scale_WACV_2021_supplemental.zip | 2012.00914 | cvf | @InProceedings{Corona_2021_WACV,
author = {Corona, Kellie and Osterdahl, Katie and Collins, Roderic and Hoogs, Anthony},
title = {MEVA: A Large-Scale Multiview, Multimodal Video Dataset for Activity Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vis... | We present the Multiview Extended Video with Activities (MEVA) dataset, a new and very-large-scale dataset for human activity recognition. Existing security datasets either focus on activity counts by aggregating public video disseminated due to its content, which typically excludes same-scene background video, or they... |
Hussain_Adversarial_Deepfakes_Evaluating_Vulnerability_of_Deepfake_Detectors_to_Adversarial_Examples_WACV_2021_paper | Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples | [
"Shehzeen Hussain",
"Paarth Neekhara",
"Malhar Jere",
"Farinaz Koushanfar",
"Julian McAuley"
] | https://openaccess.thecvf.com/content/WACV2021/html/Hussain_Adversarial_Deepfakes_Evaluating_Vulnerability_of_Deepfake_Detectors_to_Adversarial_Examples_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Hussain_Adversarial_Deepfakes_Evaluating_Vulnerability_of_Deepfake_Detectors_to_Adversarial_Examples_WACV_2021_paper.pdf | null | 2002.12749 | cvf | @InProceedings{Hussain_2021_WACV,
author = {Hussain, Shehzeen and Neekhara, Paarth and Jere, Malhar and Koushanfar, Farinaz and McAuley, Julian},
title = {Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples},
booktitle = {Proceedings of the IEEE/CVF Winter Co... | Recent advances in video manipulation techniques have made the generation of fake videos more accessible than ever before. Manipulated videos can fuel disinformation and reduce trust in media. Therefore detection of fake videos has garnered immense interest in academia and industry. Recently developed Deepfake detectio... |
Zhang_PNPDet_Efficient_Few-Shot_Detection_Without_Forgetting_via_Plug-and-Play_Sub-Networks_WACV_2021_paper | PNPDet: Efficient Few-Shot Detection Without Forgetting via Plug-and-Play Sub-Networks | [
"Gongjie Zhang",
"Kaiwen Cui",
"Rongliang Wu",
"Shijian Lu",
"Yonghong Tian"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_PNPDet_Efficient_Few-Shot_Detection_Without_Forgetting_via_Plug-and-Play_Sub-Networks_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_PNPDet_Efficient_Few-Shot_Detection_Without_Forgetting_via_Plug-and-Play_Sub-Networks_WACV_2021_paper.pdf | null | null | null | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Gongjie and Cui, Kaiwen and Wu, Rongliang and Lu, Shijian and Tian, Yonghong},
title = {PNPDet: Efficient Few-Shot Detection Without Forgetting via Plug-and-Play Sub-Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications ... | The human visual system can detect objects of unseen categories from merely a few examples. However, such capability remains absent in state-of-the-art detectors. To bridge this gap, several attempts have been proposed to perform few-shot detection by incorporating meta-learning techniques. Such methods can improve det... |
Peer_Conflicting_Bundles_Adapting_Architectures_Towards_the_Improved_Training_of_Deep_WACV_2021_paper | Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks | [
"David Peer",
"Sebastian Stabinger",
"Antonio Rodriguez-Sanchez"
] | https://openaccess.thecvf.com/content/WACV2021/html/Peer_Conflicting_Bundles_Adapting_Architectures_Towards_the_Improved_Training_of_Deep_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Peer_Conflicting_Bundles_Adapting_Architectures_Towards_the_Improved_Training_of_Deep_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Peer_Conflicting_Bundles_Adapting_WACV_2021_supplemental.pdf | 2011.02956 | title_snapshot | @InProceedings{Peer_2021_WACV,
author = {Peer, David and Stabinger, Sebastian and Rodriguez-Sanchez, Antonio},
title = {Conflicting Bundles: Adapting Architectures Towards the Improved Training of Deep Neural Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Com... | Designing neural network architectures is a challenging task and knowing which specific layers of a model must be adapted to improve the performance is almost a mystery. In this paper, we introduce a novel theory and metric to identify layers that decrease the test accuracy of the trained models, this identification is... |
Alnaggar_Multi_Projection_Fusion_for_Real-Time_Semantic_Segmentation_of_3D_LiDAR_WACV_2021_paper | Multi Projection Fusion for Real-Time Semantic Segmentation of 3D LiDAR Point Clouds | [
"Yara Ali Alnaggar",
"Mohamed Afifi",
"Karim Amer",
"Mohamed ElHelw"
] | https://openaccess.thecvf.com/content/WACV2021/html/Alnaggar_Multi_Projection_Fusion_for_Real-Time_Semantic_Segmentation_of_3D_LiDAR_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Alnaggar_Multi_Projection_Fusion_for_Real-Time_Semantic_Segmentation_of_3D_LiDAR_WACV_2021_paper.pdf | null | 2011.01974 | cvf | @InProceedings{Alnaggar_2021_WACV,
author = {Alnaggar, Yara Ali and Afifi, Mohamed and Amer, Karim and ElHelw, Mohamed},
title = {Multi Projection Fusion for Real-Time Semantic Segmentation of 3D LiDAR Point Clouds},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comput... | Semantic segmentation of 3D point cloud data is essential for enhanced high-level perception in autonomous platforms. Furthermore, given the increasing deployment of LiDAR sensors onboard of cars and drones, a special emphasis is also placed on non-computationally intensive algorithms that operate on mobile GPUs. Previ... |
Bradley_Cinematic-L1_Video_Stabilization_With_a_Log-Homography_Model_WACV_2021_paper | Cinematic-L1 Video Stabilization With a Log-Homography Model | [
"Arwen Bradley",
"Jason Klivington",
"Joseph Triscari",
"Rudolph van der Merwe"
] | https://openaccess.thecvf.com/content/WACV2021/html/Bradley_Cinematic-L1_Video_Stabilization_With_a_Log-Homography_Model_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Bradley_Cinematic-L1_Video_Stabilization_With_a_Log-Homography_Model_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Bradley_Cinematic-L1_Video_Stabilization_WACV_2021_supplemental.zip | 2011.08144 | cvf | @InProceedings{Bradley_2021_WACV,
author = {Bradley, Arwen and Klivington, Jason and Triscari, Joseph and van der Merwe, Rudolph},
title = {Cinematic-L1 Video Stabilization With a Log-Homography Model},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WAC... | We present a method for stabilizing handheld video that simulates the camera motions cinematographers achieve with equipment like tripods, dollies, and Steadicams. We formulate a constrained convex optimization problem minimizing the L1-norm of the first three derivatives of the stabilized motion. Our approach extends ... |
Shao_Temporal_Context_Aggregation_for_Video_Retrieval_With_Contrastive_Learning_WACV_2021_paper | Temporal Context Aggregation for Video Retrieval With Contrastive Learning | [
"Jie Shao",
"Xin Wen",
"Bingchen Zhao",
"Xiangyang Xue"
] | https://openaccess.thecvf.com/content/WACV2021/html/Shao_Temporal_Context_Aggregation_for_Video_Retrieval_With_Contrastive_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Shao_Temporal_Context_Aggregation_for_Video_Retrieval_With_Contrastive_Learning_WACV_2021_paper.pdf | null | 2008.01334 | cvf | @InProceedings{Shao_2021_WACV,
author = {Shao, Jie and Wen, Xin and Zhao, Bingchen and Xue, Xiangyang},
title = {Temporal Context Aggregation for Video Retrieval With Contrastive Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mont... | The current research focus on Content-Based Video Retrieval requires higher-level video representation describing the long-range semantic dependencies of relevant incidents, events, etc. However, existing methods commonly process the frames of a video as individual images or short clips, making the modeling of long-ran... |
Tan_TrustMAE_A_Noise-Resilient_Defect_Classification_Framework_Using_Memory-Augmented_Auto-Encoders_With_WACV_2021_paper | TrustMAE: A Noise-Resilient Defect Classification Framework Using Memory-Augmented Auto-Encoders With Trust Regions | [
"Daniel Stanley Tan",
"Yi-Chun Chen",
"Trista Pei-Chun Chen",
"Wei-Chao Chen"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tan_TrustMAE_A_Noise-Resilient_Defect_Classification_Framework_Using_Memory-Augmented_Auto-Encoders_With_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tan_TrustMAE_A_Noise-Resilient_Defect_Classification_Framework_Using_Memory-Augmented_Auto-Encoders_With_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Tan_TrustMAE_A_Noise-Resilient_WACV_2021_supplemental.pdf | 2012.14629 | title_snapshot | @InProceedings{Tan_2021_WACV,
author = {Tan, Daniel Stanley and Chen, Yi-Chun and Chen, Trista Pei-Chun and Chen, Wei-Chao},
title = {TrustMAE: A Noise-Resilient Defect Classification Framework Using Memory-Augmented Auto-Encoders With Trust Regions},
booktitle = {Proceedings of the IEEE/CVF Winter C... | In this paper, we propose a framework called TrustMAE to address the problem of product defect classification. Instead of relying on defective images that are difficult to collect and laborious to label, our framework can accept datasets with unlabeled images. Moreover, unlike most anomaly detection methods, our approa... |
Hegde_Visual_Speech_Enhancement_Without_a_Real_Visual_Stream_WACV_2021_paper | Visual Speech Enhancement Without a Real Visual Stream | [
"Sindhu B. Hegde",
"K.R. Prajwal",
"Rudrabha Mukhopadhyay",
"Vinay P. Namboodiri",
"C.V. Jawahar"
] | https://openaccess.thecvf.com/content/WACV2021/html/Hegde_Visual_Speech_Enhancement_Without_a_Real_Visual_Stream_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Hegde_Visual_Speech_Enhancement_Without_a_Real_Visual_Stream_WACV_2021_paper.pdf | null | 2012.10852 | cvf | @InProceedings{Hegde_2021_WACV,
author = {Hegde, Sindhu B. and Prajwal, K.R. and Mukhopadhyay, Rudrabha and Namboodiri, Vinay P. and Jawahar, C.V.},
title = {Visual Speech Enhancement Without a Real Visual Stream},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer... | In this work, we re-think the task of speech enhancement in unconstrained real-world environments. Current state-of-the-art methods use only the audio stream and are limited in their performance in a wide range of real-world noises. Recent works using lip movements as additional cues improve the quality of generated sp... |
Cai_Dynamic_Routing_Networks_WACV_2021_paper | Dynamic Routing Networks | [
"Shaofeng Cai",
"Yao Shu",
"Wei Wang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Cai_Dynamic_Routing_Networks_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Cai_Dynamic_Routing_Networks_WACV_2021_paper.pdf | null | 1905.04849 | cvf | @InProceedings{Cai_2021_WACV,
author = {Cai, Shaofeng and Shu, Yao and Wang, Wei},
title = {Dynamic Routing Networks},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pages = {3588-3597}
... | The deployment of deep neural networks in real-world applications is mostly restricted by their high inference costs. Extensive efforts have been made to improve the accuracy with expert-designed or algorithm-searched architectures. However, the incremental improvement is typically achieved with increasingly more expen... |
Lutz_Foreground_Color_Prediction_Through_Inverse_Compositing_WACV_2021_paper | Foreground Color Prediction Through Inverse Compositing | [
"Sebastian Lutz",
"Aljosa Smolic"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lutz_Foreground_Color_Prediction_Through_Inverse_Compositing_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lutz_Foreground_Color_Prediction_Through_Inverse_Compositing_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Lutz_Foreground_Color_Prediction_WACV_2021_supplemental.pdf | 2103.13423 | title_snapshot | @InProceedings{Lutz_2021_WACV,
author = {Lutz, Sebastian and Smolic, Aljosa},
title = {Foreground Color Prediction Through Inverse Compositing},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
... | In natural image matting, the goal is to estimate the opacity of the foreground object in the image. This opacity controls the way the foreground and background is blended in transparent regions. In recent years, advances in deep learning have led to many natural image matting algorithms that have achieved outstanding ... |
Voigtlaender_Reducing_the_Annotation_Effort_for_Video_Object_Segmentation_Datasets_WACV_2021_paper | Reducing the Annotation Effort for Video Object Segmentation Datasets | [
"Paul Voigtlaender",
"Lishu Luo",
"Chun Yuan",
"Yong Jiang",
"Bastian Leibe"
] | https://openaccess.thecvf.com/content/WACV2021/html/Voigtlaender_Reducing_the_Annotation_Effort_for_Video_Object_Segmentation_Datasets_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Voigtlaender_Reducing_the_Annotation_Effort_for_Video_Object_Segmentation_Datasets_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Voigtlaender_Reducing_the_Annotation_WACV_2021_supplemental.zip | 2011.01142 | cvf | @InProceedings{Voigtlaender_2021_WACV,
author = {Voigtlaender, Paul and Luo, Lishu and Yuan, Chun and Jiang, Yong and Leibe, Bastian},
title = {Reducing the Annotation Effort for Video Object Segmentation Datasets},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compute... | For further progress in video object segmentation (VOS), larger, more diverse, and more challenging datasets will be necessary. However, densely labeling every frame with pixel masks does not scale to large datasets. We use a deep convolutional network to automatically create pseudo-labels on a pixel level from much ch... |
Gong_Style_Consistent_Image_Generation_for_Nuclei_Instance_Segmentation_WACV_2021_paper | Style Consistent Image Generation for Nuclei Instance Segmentation | [
"Xuan Gong",
"Shuyan Chen",
"Baochang Zhang",
"David Doermann"
] | https://openaccess.thecvf.com/content/WACV2021/html/Gong_Style_Consistent_Image_Generation_for_Nuclei_Instance_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Gong_Style_Consistent_Image_Generation_for_Nuclei_Instance_Segmentation_WACV_2021_paper.pdf | null | null | null | @InProceedings{Gong_2021_WACV,
author = {Gong, Xuan and Chen, Shuyan and Zhang, Baochang and Doermann, David},
title = {Style Consistent Image Generation for Nuclei Instance Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | In medical image analysis, one limitation of the application of machine learning is the insufficient amount of data with detailed annotation, due primarily to high cost. Another impediment is the domain gap observed between images from different organs and different collections. The differences are even more challengin... |
Jayasundara_FlowCaps_Optical_Flow_Estimation_With_Capsule_Networks_for_Action_Recognition_WACV_2021_paper | FlowCaps: Optical Flow Estimation With Capsule Networks for Action Recognition | [
"Vinoj Jayasundara",
"Debaditya Roy",
"Basura Fernando"
] | https://openaccess.thecvf.com/content/WACV2021/html/Jayasundara_FlowCaps_Optical_Flow_Estimation_With_Capsule_Networks_for_Action_Recognition_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Jayasundara_FlowCaps_Optical_Flow_Estimation_With_Capsule_Networks_for_Action_Recognition_WACV_2021_paper.pdf | null | 2011.03958 | cvf | @InProceedings{Jayasundara_2021_WACV,
author = {Jayasundara, Vinoj and Roy, Debaditya and Fernando, Basura},
title = {FlowCaps: Optical Flow Estimation With Capsule Networks for Action Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},... | Capsule networks (CapsNets) have recently shown promise to excel in most computer vision tasks, especially pertaining to scene understanding. In this paper, we explore CapsNet's capabilities in optical flow estimation, a task at which convolutional neural networks (CNNs) have already outperformed other approaches. We p... |
Zhao_Legacy_Photo_Editing_With_Learned_Noise_Prior_WACV_2021_paper | Legacy Photo Editing With Learned Noise Prior | [
"Yuzhi Zhao",
"Lai-Man Po",
"Tingyu Lin",
"Xuehui Wang",
"Kangcheng Liu",
"Yujia Zhang",
"Wing-Yin Yu",
"Pengfei Xian",
"Jingjing Xiong"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhao_Legacy_Photo_Editing_With_Learned_Noise_Prior_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhao_Legacy_Photo_Editing_With_Learned_Noise_Prior_WACV_2021_paper.pdf | null | 2011.11309 | title_snapshot | @InProceedings{Zhao_2021_WACV,
author = {Zhao, Yuzhi and Po, Lai-Man and Lin, Tingyu and Wang, Xuehui and Liu, Kangcheng and Zhang, Yujia and Yu, Wing-Yin and Xian, Pengfei and Xiong, Jingjing},
title = {Legacy Photo Editing With Learned Noise Prior},
booktitle = {Proceedings of the IEEE/CVF Winter C... | There are quite a number of photographs captured under undesirable conditions in the last century. Thus, they are often noisy, regionally incomplete, and grayscale formatted. Conventional approaches mainly focus on one point so that those restoration results are not perceptually sharp or clean enough. To solve these pr... |
Zhang_AdarGCN_Adaptive_Aggregation_GCN_for_Few-Shot_Learning_WACV_2021_paper | AdarGCN: Adaptive Aggregation GCN for Few-Shot Learning | [
"Jianhong Zhang",
"Manli Zhang",
"Zhiwu Lu",
"Tao Xiang"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_AdarGCN_Adaptive_Aggregation_GCN_for_Few-Shot_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_AdarGCN_Adaptive_Aggregation_GCN_for_Few-Shot_Learning_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Zhang_AdarGCN_Adaptive_Aggregation_WACV_2021_supplemental.pdf | 2002.12641 | cvf | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Jianhong and Zhang, Manli and Lu, Zhiwu and Xiang, Tao},
title = {AdarGCN: Adaptive Aggregation GCN for Few-Shot Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January}... | Existing few-shot learning (FSL) methods assume that there exist sufficient training samples from source classes for knowledge transfer to target classes with few training samples. However, this assumption is often invalid, especially when it comes to fine-grained recognition. In this work, we define a new FSL setting ... |
Sensoy_Misclassification_Risk_and_Uncertainty_Quantification_in_Deep_Classifiers_WACV_2021_paper | Misclassification Risk and Uncertainty Quantification in Deep Classifiers | [
"Murat Sensoy",
"Maryam Saleki",
"Simon Julier",
"Reyhan Aydogan",
"John Reid"
] | https://openaccess.thecvf.com/content/WACV2021/html/Sensoy_Misclassification_Risk_and_Uncertainty_Quantification_in_Deep_Classifiers_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Sensoy_Misclassification_Risk_and_Uncertainty_Quantification_in_Deep_Classifiers_WACV_2021_paper.pdf | null | null | null | @InProceedings{Sensoy_2021_WACV,
author = {Sensoy, Murat and Saleki, Maryam and Julier, Simon and Aydogan, Reyhan and Reid, John},
title = {Misclassification Risk and Uncertainty Quantification in Deep Classifiers},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compute... | In this paper, we propose risk-calibrated evidential deep classifiers to reduce the costs associated with classification errors. We use two main approaches. The first is to develop methods to quantify the uncertainty of a classifier's predictions and reduce the likelihood of acting on erroneous predictions. The second ... |
Chu_A_Vector-Based_Representation_to_Enhance_Head_Pose_Estimation_WACV_2021_paper | A Vector-Based Representation to Enhance Head Pose Estimation | [
"Zhiwen Cao",
"Zongcheng Chu",
"Dongfang Liu",
"Yingjie Chen"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chu_A_Vector-Based_Representation_to_Enhance_Head_Pose_Estimation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chu_A_Vector-Based_Representation_to_Enhance_Head_Pose_Estimation_WACV_2021_paper.pdf | null | 2010.07184 | cvf | @InProceedings{Cao_2021_WACV,
author = {Cao, Zhiwen and Chu, Zongcheng and Liu, Dongfang and Chen, Yingjie},
title = {A Vector-Based Representation to Enhance Head Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = ... | This paper proposes to use the three vectors in a rotation matrix as the representation in head pose estimation and develops a new neural network based on the characteristic of such representation. We address two potential issues existed in current head pose estimation works: 1. Public datasets for head pose estimation... |
Jafarzadeh_Automatic_Open-World_Reliability_Assessment_WACV_2021_paper | Automatic Open-World Reliability Assessment | [
"Mohsen Jafarzadeh",
"Touqeer Ahmad",
"Akshay Raj Dhamija",
"Chunchun Li",
"Steve Cruz",
"Terrance E. Boult"
] | https://openaccess.thecvf.com/content/WACV2021/html/Jafarzadeh_Automatic_Open-World_Reliability_Assessment_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Jafarzadeh_Automatic_Open-World_Reliability_Assessment_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Jafarzadeh_Automatic_Open-World_Reliability_WACV_2021_supplemental.pdf | 2011.05506 | cvf | @InProceedings{Jafarzadeh_2021_WACV,
author = {Jafarzadeh, Mohsen and Ahmad, Touqeer and Dhamija, Akshay Raj and Li, Chunchun and Cruz, Steve and Boult, Terrance E.},
title = {Automatic Open-World Reliability Assessment},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of C... | Image classification in the open-world must handle out-of-distribution (OOD) images. Systems should ideally reject OOD images, or they will map atop of known classes and reduce reliability. Using open-set classifiers that can reject OOD inputs can help. However, optimal accuracy of open-set classifiers depend on the fr... |
Schuster_SSGP_Sparse_Spatial_Guided_Propagation_for_Robust_and_Generic_Interpolation_WACV_2021_paper | SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation | [
"Rene Schuster",
"Oliver Wasenmuller",
"Christian Unger",
"Didier Stricker"
] | https://openaccess.thecvf.com/content/WACV2021/html/Schuster_SSGP_Sparse_Spatial_Guided_Propagation_for_Robust_and_Generic_Interpolation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Schuster_SSGP_Sparse_Spatial_Guided_Propagation_for_Robust_and_Generic_Interpolation_WACV_2021_paper.pdf | null | 2008.09346 | cvf | @InProceedings{Schuster_2021_WACV,
author = {Schuster, Rene and Wasenmuller, Oliver and Unger, Christian and Stricker, Didier},
title = {SSGP: Sparse Spatial Guided Propagation for Robust and Generic Interpolation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Compute... | Interpolation of sparse pixel information towards a dense target resolution finds its application across multiple disciplines in computer vision. State-of-the-art interpolation of motion fields applies model-based interpolation that makes use of edge information extracted from the target image. For depth completion, da... |
Anwaar_Compositional_Learning_of_Image-Text_Query_for_Image_Retrieval_WACV_2021_paper | Compositional Learning of Image-Text Query for Image Retrieval | [
"Muhammad Umer Anwaar",
"Egor Labintcev",
"Martin Kleinsteuber"
] | https://openaccess.thecvf.com/content/WACV2021/html/Anwaar_Compositional_Learning_of_Image-Text_Query_for_Image_Retrieval_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Anwaar_Compositional_Learning_of_Image-Text_Query_for_Image_Retrieval_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Anwaar_Compositional_Learning_of_WACV_2021_supplemental.pdf | 2006.11149 | cvf | @InProceedings{Anwaar_2021_WACV,
author = {Anwaar, Muhammad Umer and Labintcev, Egor and Kleinsteuber, Martin},
title = {Compositional Learning of Image-Text Query for Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | In this paper, we investigate the problem of retrieving images from a database based on a multi-modal (image-text) query. Specifically, the query text prompts some modification in the query image and the task is to retrieve images with the desired modifications. For instance, a user of an e-commerce platform is interes... |
Kishida_Object_Recognition_With_Continual_Open_Set_Domain_Adaptation_for_Home_WACV_2021_paper | Object Recognition With Continual Open Set Domain Adaptation for Home Robot | [
"Ikki Kishida",
"Hong Chen",
"Masaki Baba",
"Jiren Jin",
"Ayako Amma",
"Hideki Nakayama"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kishida_Object_Recognition_With_Continual_Open_Set_Domain_Adaptation_for_Home_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kishida_Object_Recognition_With_Continual_Open_Set_Domain_Adaptation_for_Home_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Kishida_Object_Recognition_With_WACV_2021_supplemental.pdf | null | null | @InProceedings{Kishida_2021_WACV,
author = {Kishida, Ikki and Chen, Hong and Baba, Masaki and Jin, Jiren and Amma, Ayako and Nakayama, Hideki},
title = {Object Recognition With Continual Open Set Domain Adaptation for Home Robot},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicat... | Object recognition ability is indispensable for robots to act like humans in a home environment. For example, when considering an object searching task, humans can recognize a naturally arranged object previously held in their hands while ignoring never observed objects. Even in such a simple task, we need to deal with... |
Figueiredo_MoRe_A_Large-Scale_Motorcycle_Re-Identification_Dataset_WACV_2021_paper | MoRe: A Large-Scale Motorcycle Re-Identification Dataset | [
"Augusto Figueiredo",
"Johnata Brayan",
"Renan Oliveira Reis",
"Raphael Prates",
"William Robson Schwartz"
] | https://openaccess.thecvf.com/content/WACV2021/html/Figueiredo_MoRe_A_Large-Scale_Motorcycle_Re-Identification_Dataset_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Figueiredo_MoRe_A_Large-Scale_Motorcycle_Re-Identification_Dataset_WACV_2021_paper.pdf | null | null | null | @InProceedings{Figueiredo_2021_WACV,
author = {Figueiredo, Augusto and Brayan, Johnata and Reis, Renan Oliveira and Prates, Raphael and Schwartz, William Robson},
title = {MoRe: A Large-Scale Motorcycle Re-Identification Dataset},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applicat... | Motorcycles are often related to transit and criminal issues due to its abundance in the transit. Despite its importance, motorcycles are a seldom addressed problem in the computer vision community. We credit this problem to the lack of large-scale datasets and strong baseline models. Therefore, we present the first la... |
Anderson_Have_Fun_Storming_the_Castles_WACV_2021_paper | Have Fun Storming the Castle(s)! | [
"Connor Anderson",
"Adam Teuscher",
"Elizabeth Anderson",
"Alysia Larsen",
"Josh Shirley",
"Ryan Farrell"
] | https://openaccess.thecvf.com/content/WACV2021/html/Anderson_Have_Fun_Storming_the_Castles_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Anderson_Have_Fun_Storming_the_Castles_WACV_2021_paper.pdf | null | null | null | @InProceedings{Anderson_2021_WACV,
author = {Anderson, Connor and Teuscher, Adam and Anderson, Elizabeth and Larsen, Alysia and Shirley, Josh and Farrell, Ryan},
title = {Have Fun Storming the Castle(s)!},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (... | In recent years, large-scale datasets, each typically tailored to a particular problem, have become a critical factor towards fueling rapid progress in the field of computer vision. This paper describes a valuable new dataset that should accelerate research efforts on problems such as fine-grained classification, insta... |
Tsutsui_Whose_Hand_Is_This_Person_Identification_From_Egocentric_Hand_Gestures_WACV_2021_paper | Whose Hand Is This? Person Identification From Egocentric Hand Gestures | [
"Satoshi Tsutsui",
"Yanwei Fu",
"David J. Crandall"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tsutsui_Whose_Hand_Is_This_Person_Identification_From_Egocentric_Hand_Gestures_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tsutsui_Whose_Hand_Is_This_Person_Identification_From_Egocentric_Hand_Gestures_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Tsutsui_Whose_Hand_Is_WACV_2021_supplemental.pdf | 2011.08900 | cvf | @InProceedings{Tsutsui_2021_WACV,
author = {Tsutsui, Satoshi and Fu, Yanwei and Crandall, David J.},
title = {Whose Hand Is This? Person Identification From Egocentric Hand Gestures},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Recognizing people by faces and other biometrics has been extensively studied in computer vision. But these techniques do not work for identifying the wearer of an egocentric (first-person) camera because that person rarely (if ever) appears in their own first-person view. But while one's own face is not frequently vis... |
Chen_Multi-Level_Generative_Chaotic_Recurrent_Network_for_Image_Inpainting_WACV_2021_paper | Multi-Level Generative Chaotic Recurrent Network for Image Inpainting | [
"Cong Chen",
"Amos Abbott",
"Daniel Stilwell"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chen_Multi-Level_Generative_Chaotic_Recurrent_Network_for_Image_Inpainting_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chen_Multi-Level_Generative_Chaotic_Recurrent_Network_for_Image_Inpainting_WACV_2021_paper.pdf | null | null | null | @InProceedings{Chen_2021_WACV,
author = {Chen, Cong and Abbott, Amos and Stilwell, Daniel},
title = {Multi-Level Generative Chaotic Recurrent Network for Image Inpainting},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January}... | This paper presents a novel multi-level generative chaotic Recurrent Neural Network (RNN) for image inpainting. This technique utilizes a general framework with multiple chaotic RNN that makes learning the image prior from a single corrupted image more robust and efficient. The proposed network utilizes a randomly-init... |
Khademi_Self-Supervised_Poisson-Gaussian_Denoising_WACV_2021_paper | Self-Supervised Poisson-Gaussian Denoising | [
"Wesley Khademi",
"Sonia Rao",
"Clare Minnerath",
"Guy Hagen",
"Jonathan Ventura"
] | https://openaccess.thecvf.com/content/WACV2021/html/Khademi_Self-Supervised_Poisson-Gaussian_Denoising_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Khademi_Self-Supervised_Poisson-Gaussian_Denoising_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Khademi_Self-Supervised_Poisson-Gaussian_Denoising_WACV_2021_supplemental.pdf | 2002.09558 | cvf | @InProceedings{Khademi_2021_WACV,
author = {Khademi, Wesley and Rao, Sonia and Minnerath, Clare and Hagen, Guy and Ventura, Jonathan},
title = {Self-Supervised Poisson-Gaussian Denoising},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month... | We extend the blindspot model for self-supervised denoising to handle Poisson-Gaussian noise and introduce an improved training scheme that avoids hyperparameters and adapts the denoiser to the test data. Self-supervised models for denoising learn to denoise from only noisy data and do not require corresponding clean i... |
Prokudin_SMPLpix_Neural_Avatars_From_3D_Human_Models_WACV_2021_paper | SMPLpix: Neural Avatars From 3D Human Models | [
"Sergey Prokudin",
"Michael J. Black",
"Javier Romero"
] | https://openaccess.thecvf.com/content/WACV2021/html/Prokudin_SMPLpix_Neural_Avatars_From_3D_Human_Models_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Prokudin_SMPLpix_Neural_Avatars_From_3D_Human_Models_WACV_2021_paper.pdf | null | 2008.06872 | cvf | @InProceedings{Prokudin_2021_WACV,
author = {Prokudin, Sergey and Black, Michael J. and Romero, Javier},
title = {SMPLpix: Neural Avatars From 3D Human Models},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | Recent advances in deep generative models have led to an unprecedented level of realism for synthetically generated images of humans. However, one of the remaining fundamental limitations of these models is the ability to flexibly control the generative process, e.g. change the camera and human pose while retaining the... |
Hauri_Multi-Modal_Trajectory_Prediction_of_NBA_Players_WACV_2021_paper | Multi-Modal Trajectory Prediction of NBA Players | [
"Sandro Hauri",
"Nemanja Djuric",
"Vladan Radosavljevic",
"Slobodan Vucetic"
] | https://openaccess.thecvf.com/content/WACV2021/html/Hauri_Multi-Modal_Trajectory_Prediction_of_NBA_Players_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Hauri_Multi-Modal_Trajectory_Prediction_of_NBA_Players_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Hauri_Multi-Modal_Trajectory_Prediction_WACV_2021_supplemental.zip | 2008.07870 | cvf | @InProceedings{Hauri_2021_WACV,
author = {Hauri, Sandro and Djuric, Nemanja and Radosavljevic, Vladan and Vucetic, Slobodan},
title = {Multi-Modal Trajectory Prediction of NBA Players},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | National Basketball Association (NBA) players are highly motivated and skilled experts that solve complex decision making problems at every time point during a game. As a step towards understanding how players make their decisions, we focus on their movement trajectories during games. We propose a method that captures ... |
Patil_Multi-Frame_Recurrent_Adversarial_Network_for_Moving_Object_Segmentation_WACV_2021_paper | Multi-Frame Recurrent Adversarial Network for Moving Object Segmentation | [
"Prashant W. Patil",
"Akshay Dudhane",
"Subrahmanyam Murala"
] | https://openaccess.thecvf.com/content/WACV2021/html/Patil_Multi-Frame_Recurrent_Adversarial_Network_for_Moving_Object_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Patil_Multi-Frame_Recurrent_Adversarial_Network_for_Moving_Object_Segmentation_WACV_2021_paper.pdf | null | null | null | @InProceedings{Patil_2021_WACV,
author = {Patil, Prashant W. and Dudhane, Akshay and Murala, Subrahmanyam},
title = {Multi-Frame Recurrent Adversarial Network for Moving Object Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
mo... | Moving object segmentation (MOS) in different practical scenarios like weather degraded, dynamic background, etc. videos is a challenging and high demanding task for various computer vision applications. Existing supervised approaches achieve remarkable performance with complicated training or extensive fine-tuning or ... |
Moynihan_Autonomous_Tracking_for_Volumetric_Video_Sequences_WACV_2021_paper | Autonomous Tracking for Volumetric Video Sequences | [
"Matthew Moynihan",
"Susana Ruano",
"Rafael Pages",
"Aljosa Smolic"
] | https://openaccess.thecvf.com/content/WACV2021/html/Moynihan_Autonomous_Tracking_for_Volumetric_Video_Sequences_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Moynihan_Autonomous_Tracking_for_Volumetric_Video_Sequences_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Moynihan_Autonomous_Tracking_for_WACV_2021_supplemental.zip | null | null | @InProceedings{Moynihan_2021_WACV,
author = {Moynihan, Matthew and Ruano, Susana and Pages, Rafael and Smolic, Aljosa},
title = {Autonomous Tracking for Volumetric Video Sequences},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = ... | As a rapidly growing medium, volumetric video is gaining attention beyond academia, reaching industry and creative communities alike. This brings new challenges to reduce the barrier to entry from a technical and economical point of view. We present a system for robustly and autonomously performing temporally coherent ... |
Le_EDEN_Multimodal_Synthetic_Dataset_of_Enclosed_GarDEN_Scenes_WACV_2021_paper | EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes | [
"Hoang-An Le",
"Thomas Mensink",
"Partha Das",
"Sezer Karaoglu",
"Theo Gevers"
] | https://openaccess.thecvf.com/content/WACV2021/html/Le_EDEN_Multimodal_Synthetic_Dataset_of_Enclosed_GarDEN_Scenes_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Le_EDEN_Multimodal_Synthetic_Dataset_of_Enclosed_GarDEN_Scenes_WACV_2021_paper.pdf | null | 2011.04389 | cvf | @InProceedings{Le_2021_WACV,
author = {Le, Hoang-An and Mensink, Thomas and Das, Partha and Karaoglu, Sezer and Gevers, Theo},
title = {EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},... | Multimodal large-scale datasets for outdoor scenes are mostly designed for urban driving problems. The scenes are highly structured and semantically different from scenarios seen in nature-centered scenes such as gardens or parks. To promote machine learning methods for nature-oriented applications, such as agriculture... |
Chang_Single_Image_Reflection_Removal_With_Edge_Guidance_Reflection_Classifier_and_WACV_2021_paper | Single Image Reflection Removal With Edge Guidance, Reflection Classifier, and Recurrent Decomposition | [
"Ya-Chu Chang",
"Chia-Ni Lu",
"Chia-Chi Cheng",
"Wei-Chen Chiu"
] | https://openaccess.thecvf.com/content/WACV2021/html/Chang_Single_Image_Reflection_Removal_With_Edge_Guidance_Reflection_Classifier_and_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Chang_Single_Image_Reflection_Removal_With_Edge_Guidance_Reflection_Classifier_and_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Chang_Single_Image_Reflection_WACV_2021_supplemental.pdf | null | null | @InProceedings{Chang_2021_WACV,
author = {Chang, Ya-Chu and Lu, Chia-Ni and Cheng, Chia-Chi and Chiu, Wei-Chen},
title = {Single Image Reflection Removal With Edge Guidance, Reflection Classifier, and Recurrent Decomposition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications... | Removing undesired reflection from an image captured through a glass window is a notable task in computer vision. In this paper, we propose a novel model with auxiliary techniques to tackle the problem of single image reflection removal. Our model takes a reflection contaminated image as input, and decomposes it into t... |
Zhu_Utilizing_Every_Image_Object_for_Semi-Supervised_Phrase_Grounding_WACV_2021_paper | Utilizing Every Image Object for Semi-Supervised Phrase Grounding | [
"Haidong Zhu",
"Arka Sadhu",
"Zhaoheng Zheng",
"Ram Nevatia"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhu_Utilizing_Every_Image_Object_for_Semi-Supervised_Phrase_Grounding_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhu_Utilizing_Every_Image_Object_for_Semi-Supervised_Phrase_Grounding_WACV_2021_paper.pdf | null | 2011.02655 | cvf | @InProceedings{Zhu_2021_WACV,
author = {Zhu, Haidong and Sadhu, Arka and Zheng, Zhaoheng and Nevatia, Ram},
title = {Utilizing Every Image Object for Semi-Supervised Phrase Grounding},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Phrase grounding models localize an object in the image given a referring expression. The annotated language queries available during training are limited, which also limits the variations of language combinations that a model can see during training. In this paper, we study the case applying objects without labeled qu... |
Zhang_Guided_Attentive_Feature_Fusion_for_Multispectral_Pedestrian_Detection_WACV_2021_paper | Guided Attentive Feature Fusion for Multispectral Pedestrian Detection | [
"Heng Zhang",
"Elisa Fromont",
"Sebastien Lefevre",
"Bruno Avignon"
] | https://openaccess.thecvf.com/content/WACV2021/html/Zhang_Guided_Attentive_Feature_Fusion_for_Multispectral_Pedestrian_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Zhang_Guided_Attentive_Feature_Fusion_for_Multispectral_Pedestrian_Detection_WACV_2021_paper.pdf | null | null | null | @InProceedings{Zhang_2021_WACV,
author = {Zhang, Heng and Fromont, Elisa and Lefevre, Sebastien and Avignon, Bruno},
title = {Guided Attentive Feature Fusion for Multispectral Pedestrian Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},... | Multispectral image pairs can provide complementary visual information, making pedestrian detection systems more robust and reliable. To benefit from both RGB and thermal IR modalities, we introduce a novel attentive multispectral feature fusion approach. Under the guidance of the inter- and intra-modality attention mo... |
Suwanwimolkul_Learning_of_Low-Level_Feature_Keypoints_for_Accurate_and_Robust_Detection_WACV_2021_paper | Learning of Low-Level Feature Keypoints for Accurate and Robust Detection | [
"Suwichaya Suwanwimolkul",
"Satoshi Komorita",
"Kazuyuki Tasaka"
] | https://openaccess.thecvf.com/content/WACV2021/html/Suwanwimolkul_Learning_of_Low-Level_Feature_Keypoints_for_Accurate_and_Robust_Detection_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Suwanwimolkul_Learning_of_Low-Level_Feature_Keypoints_for_Accurate_and_Robust_Detection_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Suwanwimolkul_Learning_of_Low-Level_WACV_2021_supplemental.pdf | null | null | @InProceedings{Suwanwimolkul_2021_WACV,
author = {Suwanwimolkul, Suwichaya and Komorita, Satoshi and Tasaka, Kazuyuki},
title = {Learning of Low-Level Feature Keypoints for Accurate and Robust Detection},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (W... | Joint learning of feature descriptor and detector has offered promising 3D reconstruction results; however, they often lack the low-level feature awareness, which causes low accuracy in matched keypoint locations. The others employed fixed operations to select the keypoints, but the selected keypoints may not correspon... |
Babicz_Receptive_Field_Size_Optimization_With_Continuous_Time_Pooling_WACV_2021_paper | Receptive Field Size Optimization With Continuous Time Pooling | [
"Dora Babicz",
"Soma Kontar",
"Mark Peto",
"Andras Fulop",
"Gergely Szabo",
"Andras Horvath"
] | https://openaccess.thecvf.com/content/WACV2021/html/Babicz_Receptive_Field_Size_Optimization_With_Continuous_Time_Pooling_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Babicz_Receptive_Field_Size_Optimization_With_Continuous_Time_Pooling_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Babicz_Receptive_Field_Size_WACV_2021_supplemental.zip | 2011.00869 | cvf | @InProceedings{Babicz_2021_WACV,
author = {Babicz, Dora and Kontar, Soma and Peto, Mark and Fulop, Andras and Szabo, Gergely and Horvath, Andras},
title = {Receptive Field Size Optimization With Continuous Time Pooling},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Co... | Pooling operation is a cornerstone element of convolutional neural networks. These elements generate receptive fields for neurons, in which local perturbations should have minimal effect on the output activations, increasing robustness and invariance of the whole network. In this paper we will present an altered versio... |
Akiva_AI_on_the_Bog_Monitoring_and_Evaluating_Cranberry_Crop_Risk_WACV_2021_paper | AI on the Bog: Monitoring and Evaluating Cranberry Crop Risk | [
"Peri Akiva",
"Benjamin Planche",
"Aditi Roy",
"Kristin Dana",
"Peter Oudemans",
"Michael Mars"
] | https://openaccess.thecvf.com/content/WACV2021/html/Akiva_AI_on_the_Bog_Monitoring_and_Evaluating_Cranberry_Crop_Risk_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Akiva_AI_on_the_Bog_Monitoring_and_Evaluating_Cranberry_Crop_Risk_WACV_2021_paper.pdf | null | 2011.04064 | cvf | @InProceedings{Akiva_2021_WACV,
author = {Akiva, Peri and Planche, Benjamin and Roy, Aditi and Dana, Kristin and Oudemans, Peter and Mars, Michael},
title = {AI on the Bog: Monitoring and Evaluating Cranberry Crop Risk},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Co... | Machine vision for precision agriculture has attracted considerable research interest in recent years. The goal of this paper is to develop an end-end cranberry health monitoring system to enable and support real time cranberry over-heating assessment to facilitate informed decisions that may sustain the economic viabi... |
Dabral_Exploration_of_Spatial_and_Temporal_Modeling_Alternatives_for_HOI_WACV_2021_paper | Exploration of Spatial and Temporal Modeling Alternatives for HOI | [
"Rishabh Dabral",
"Srijon Sarkar",
"Sai Praneeth Reddy",
"Ganesh Ramakrishnan"
] | https://openaccess.thecvf.com/content/WACV2021/html/Dabral_Exploration_of_Spatial_and_Temporal_Modeling_Alternatives_for_HOI_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Dabral_Exploration_of_Spatial_and_Temporal_Modeling_Alternatives_for_HOI_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Dabral_Exploration_of_Spatial_WACV_2021_supplemental.zip | null | null | @InProceedings{Dabral_2021_WACV,
author = {Dabral, Rishabh and Sarkar, Srijon and Reddy, Sai Praneeth and Ramakrishnan, Ganesh},
title = {Exploration of Spatial and Temporal Modeling Alternatives for HOI},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (... | Human-Object Interaction detection from a video clip can be considered as a special case of video-based Visual-Relationship Detection wherein the subject must be a human. Specifically, it involves detecting the humans and objects in the clip as well as the interactions between them. Conventionally, the problem has been... |
Garg_Mask_Selection_and_Propagation_for_Unsupervised_Video_Object_Segmentation_WACV_2021_paper | Mask Selection and Propagation for Unsupervised Video Object Segmentation | [
"Shubhika Garg",
"Vidit Goel"
] | https://openaccess.thecvf.com/content/WACV2021/html/Garg_Mask_Selection_and_Propagation_for_Unsupervised_Video_Object_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Garg_Mask_Selection_and_Propagation_for_Unsupervised_Video_Object_Segmentation_WACV_2021_paper.pdf | null | null | null | @InProceedings{Garg_2021_WACV,
author = {Garg, Shubhika and Goel, Vidit},
title = {Mask Selection and Propagation for Unsupervised Video Object Segmentation},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | In this work we present a novel approach for Unsupervised Video Object Segmentation, that is automatically generating instance level segmentation masks for salient objects and tracking them in a video. We efficiently handle problems present in existing methods such as drift while temporal propagation, tracking and addi... |
Babar_Where_to_Look_Mining_Complementary_Image_Regions_for_Weakly_Supervised_WACV_2021_paper | Where to Look?: Mining Complementary Image Regions for Weakly Supervised Object Localization | [
"Sadbhavana Babar",
"Sukhendu Das"
] | https://openaccess.thecvf.com/content/WACV2021/html/Babar_Where_to_Look_Mining_Complementary_Image_Regions_for_Weakly_Supervised_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Babar_Where_to_Look_Mining_Complementary_Image_Regions_for_Weakly_Supervised_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Babar_Where_to_Look_WACV_2021_supplemental.zip | null | null | @InProceedings{Babar_2021_WACV,
author = {Babar, Sadbhavana and Das, Sukhendu},
title = {Where to Look?: Mining Complementary Image Regions for Weakly Supervised Object Localization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month ... | Humans possess an innate capability of recognizing objects and their corresponding parts and confine their attention to that location in a visual scene where the object is spatially present. Recently, efforts to train machines to mimic this ability of humans in the form of weakly supervised object localization, using t... |
Pardo_RefineLoc_Iterative_Refinement_for_Weakly-Supervised_Action_Localization_WACV_2021_paper | RefineLoc: Iterative Refinement for Weakly-Supervised Action Localization | [
"Alejandro Pardo",
"Humam Alwassel",
"Fabian Caba",
"Ali Thabet",
"Bernard Ghanem"
] | https://openaccess.thecvf.com/content/WACV2021/html/Pardo_RefineLoc_Iterative_Refinement_for_Weakly-Supervised_Action_Localization_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Pardo_RefineLoc_Iterative_Refinement_for_Weakly-Supervised_Action_Localization_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Pardo_RefineLoc_Iterative_Refinement_WACV_2021_supplemental.pdf | 1904.00227 | cvf | @InProceedings{Pardo_2021_WACV,
author = {Pardo, Alejandro and Alwassel, Humam and Caba, Fabian and Thabet, Ali and Ghanem, Bernard},
title = {RefineLoc: Iterative Refinement for Weakly-Supervised Action Localization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Comp... | Video action detectors are usually trained using datasets with fully-supervised temporal annotations. Building such datasets is an expensive task. To alleviate this problem, recent methods have tried to leverage weak labeling, where videos are untrimmed and only a video-level label is available. In this paper, we propo... |
Komorowski_MinkLoc3D_Point_Cloud_Based_Large-Scale_Place_Recognition_WACV_2021_paper | MinkLoc3D: Point Cloud Based Large-Scale Place Recognition | [
"Jacek Komorowski"
] | https://openaccess.thecvf.com/content/WACV2021/html/Komorowski_MinkLoc3D_Point_Cloud_Based_Large-Scale_Place_Recognition_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Komorowski_MinkLoc3D_Point_Cloud_Based_Large-Scale_Place_Recognition_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Komorowski_MinkLoc3D_Point_Cloud_WACV_2021_supplemental.pdf | 2011.04530 | cvf | @InProceedings{Komorowski_2021_WACV,
author = {Komorowski, Jacek},
title = {MinkLoc3D: Point Cloud Based Large-Scale Place Recognition},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2021},
pages ... | The paper presents a learning-based method for computing a discriminative 3D point cloud descriptor for place recognition purposes. Existing methods, such as PointNetVLAD, are based on unordered point cloud representation. They use PointNet as the first processing step to extract local features, which are later aggrega... |
Wang_Towards_Precise_Intra-Camera_Supervised_Person_Re-Identification_WACV_2021_paper | Towards Precise Intra-Camera Supervised Person Re-Identification | [
"Menglin Wang",
"Baisheng Lai",
"Haokun Chen",
"Jianqiang Huang",
"Xiaojin Gong",
"Xian-Sheng Hua"
] | https://openaccess.thecvf.com/content/WACV2021/html/Wang_Towards_Precise_Intra-Camera_Supervised_Person_Re-Identification_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Wang_Towards_Precise_Intra-Camera_Supervised_Person_Re-Identification_WACV_2021_paper.pdf | null | 2002.04932 | cvf | @InProceedings{Wang_2021_WACV,
author = {Wang, Menglin and Lai, Baisheng and Chen, Haokun and Huang, Jianqiang and Gong, Xiaojin and Hua, Xian-Sheng},
title = {Towards Precise Intra-Camera Supervised Person Re-Identification},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications... | Intra-camera supervision (ICS) for person re-identification (Re-ID) assumes that identity labels are independently annotated within each camera view and no inter-camera identity association is labeled. It is a new setting proposed recently to reduce the burden of annotation while expect to maintain desirable Re-ID perf... |
Kilickaya_Structured_Visual_Search_via_Composition-Aware_Learning_WACV_2021_paper | Structured Visual Search via Composition-Aware Learning | [
"Mert Kilickaya",
"Arnold W.M. Smeulders"
] | https://openaccess.thecvf.com/content/WACV2021/html/Kilickaya_Structured_Visual_Search_via_Composition-Aware_Learning_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Kilickaya_Structured_Visual_Search_via_Composition-Aware_Learning_WACV_2021_paper.pdf | null | 2010.14438 | cvf | @InProceedings{Kilickaya_2021_WACV,
author = {Kilickaya, Mert and Smeulders, Arnold W.M.},
title = {Structured Visual Search via Composition-Aware Learning},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year ... | This paper studies visual search using structured queries. The structure is in the form of a 2D composition that encodes the position and the category of the objects. The transformation of the position and the category of the objects leads to a continuous-valued relationship between visual compositions, which carries h... |
Lee_Learning_to_Distill_Convolutional_Features_Into_Compact_Local_Descriptors_WACV_2021_paper | Learning to Distill Convolutional Features Into Compact Local Descriptors | [
"Jongmin Lee",
"Yoonwoo Jeong",
"Seungwook Kim",
"Juhong Min",
"Minsu Cho"
] | https://openaccess.thecvf.com/content/WACV2021/html/Lee_Learning_to_Distill_Convolutional_Features_Into_Compact_Local_Descriptors_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Lee_Learning_to_Distill_Convolutional_Features_Into_Compact_Local_Descriptors_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Lee_Learning_to_Distill_WACV_2021_supplemental.pdf | null | null | @InProceedings{Lee_2021_WACV,
author = {Lee, Jongmin and Jeong, Yoonwoo and Kim, Seungwook and Min, Juhong and Cho, Minsu},
title = {Learning to Distill Convolutional Features Into Compact Local Descriptors},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Visio... | Extracting local descriptors or features is an essential step in solving image matching problems. Recent methods in the literature mainly focus on extracting effective descriptors, without much attention to the size of the descriptors. In this work, we study how to learn a compact yet effective local descriptor. The pr... |
Tang_Spatial_Context-Aware_Self-Attention_Model_for_Multi-Organ_Segmentation_WACV_2021_paper | Spatial Context-Aware Self-Attention Model for Multi-Organ Segmentation | [
"Hao Tang",
"Xingwei Liu",
"Kun Han",
"Xiaohui Xie",
"Xuming Chen",
"Huang Qian",
"Yong Liu",
"Shanlin Sun",
"Narisu Bai"
] | https://openaccess.thecvf.com/content/WACV2021/html/Tang_Spatial_Context-Aware_Self-Attention_Model_for_Multi-Organ_Segmentation_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Tang_Spatial_Context-Aware_Self-Attention_Model_for_Multi-Organ_Segmentation_WACV_2021_paper.pdf | null | 2012.09279 | cvf | @InProceedings{Tang_2021_WACV,
author = {Tang, Hao and Liu, Xingwei and Han, Kun and Xie, Xiaohui and Chen, Xuming and Qian, Huang and Liu, Yong and Sun, Shanlin and Bai, Narisu},
title = {Spatial Context-Aware Self-Attention Model for Multi-Organ Segmentation},
booktitle = {Proceedings of the IEEE/C... | Multi-organ segmentation is one of most successful applications of deep learning in medical image analysis. Deep convolutional neural nets (CNNs) have shown great promise in achieving clinically applicable image segmentation performance on CT or MRI images. State-of-the-art CNN segmentation models apply either 2D or 3D... |
Mathur_2D_to_3D_Medical_Image_Colorization_WACV_2021_paper | 2D to 3D Medical Image Colorization | [
"Aradhya Neeraj Mathur",
"Apoorv Khattar",
"Ojaswa Sharma"
] | https://openaccess.thecvf.com/content/WACV2021/html/Mathur_2D_to_3D_Medical_Image_Colorization_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Mathur_2D_to_3D_Medical_Image_Colorization_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Mathur_2D_to_3D_WACV_2021_supplemental.zip | null | null | @InProceedings{Mathur_2021_WACV,
author = {Mathur, Aradhya Neeraj and Khattar, Apoorv and Sharma, Ojaswa},
title = {2D to 3D Medical Image Colorization},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {... | Colorization involves the synthesis of colors while preserving structural content as well as the semantics of the target image. This is a well-explored problem in 2D with many state-of-the-art solutions. We explore a new challenge in the field of colorization where we aim at colorizing multi-modal 3D medical data using... |
Jain_IGSSTRCF_Importance_Guided_Sparse_Spatio-Temporal_Regularized_Correlation_Filters_for_Tracking_WACV_2021_paper | IGSSTRCF: Importance Guided Sparse Spatio-Temporal Regularized Correlation Filters for Tracking | [
"Monika Jain",
"A. V. Subramanyam",
"Simon Denman",
"Sridha Sridharan",
"Clinton Fookes"
] | https://openaccess.thecvf.com/content/WACV2021/html/Jain_IGSSTRCF_Importance_Guided_Sparse_Spatio-Temporal_Regularized_Correlation_Filters_for_Tracking_WACV_2021_paper.html | https://openaccess.thecvf.com/content/WACV2021/papers/Jain_IGSSTRCF_Importance_Guided_Sparse_Spatio-Temporal_Regularized_Correlation_Filters_for_Tracking_WACV_2021_paper.pdf | https://openaccess.thecvf.com/content/WACV2021/supplemental/Jain_IGSSTRCF_Importance_Guided_WACV_2021_supplemental.zip | null | null | @InProceedings{Jain_2021_WACV,
author = {Jain, Monika and Subramanyam, A. V. and Denman, Simon and Sridharan, Sridha and Fookes, Clinton},
title = {IGSSTRCF: Importance Guided Sparse Spatio-Temporal Regularized Correlation Filters for Tracking},
booktitle = {Proceedings of the IEEE/CVF Winter Confere... | This paper proposes a novel Importance Guided Sparse Spatio-Temporal Regularization based Correlation Filter (IGSSTRCF) tracker. Our formulation explicitly models the variations in the correlation filters and associated spatial weights in successive frames. By imposing a sparsity penalty on these variations, the formul... |
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