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0 | Towards Attack-tolerant Federated Learning via Critical Parameter Analysis | [
"Sungwon Han",
"Sungwon Park",
"Fangzhao Wu",
"Sundong Kim",
"Bin Zhu",
"Xing Xie",
"Meeyoung Cha"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Han_Towards_Attack-tolerant_Federated_Learning_via_Critical_Parameter_Analysis_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Han_Towards_Attack-tolerant_Federated_Learning_via_Critical_Parameter_Analysis_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Han_Towards_Attack-tolerant_Federated_ICCV_2023_supplemental.pdf | 2308.09318 | cvf | @InProceedings{Han_2023_ICCV,
author = {Han, Sungwon and Park, Sungwon and Wu, Fangzhao and Kim, Sundong and Zhu, Bin and Xie, Xing and Cha, Meeyoung},
title = {Towards Attack-tolerant Federated Learning via Critical Parameter Analysis},
booktitle = {Proceedings of the IEEE/CVF International Conferen... | Federated learning is used to train a shared model in a decentralized way without clients sharing private data with each other. Federated learning systems are susceptible to poisoning attacks when malicious clients send false updates to the central server. Existing defense strategies are ineffective under non-IID data ... | [
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1 | Stochastic Segmentation with Conditional Categorical Diffusion Models | [
"Lukas Zbinden",
"Lars Doorenbos",
"Theodoros Pissas",
"Adrian Thomas Huber",
"Raphael Sznitman",
"Pablo Márquez-Neila"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zbinden_Stochastic_Segmentation_with_Conditional_Categorical_Diffusion_Models_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zbinden_Stochastic_Segmentation_with_Conditional_Categorical_Diffusion_Models_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zbinden_Stochastic_Segmentation_with_ICCV_2023_supplemental.pdf | 2303.08888 | cvf | @InProceedings{Zbinden_2023_ICCV,
author = {Zbinden, Lukas and Doorenbos, Lars and Pissas, Theodoros and Huber, Adrian Thomas and Sznitman, Raphael and M\'arquez-Neila, Pablo},
title = {Stochastic Segmentation with Conditional Categorical Diffusion Models},
booktitle = {Proceedings of the IEEE/CVF In... | Semantic segmentation has made significant progress in recent years thanks to deep neural networks, but the common objective of generating a single segmentation output that accurately matches the image's content may not be suitable for safety-critical domains such as medical diagnostics and autonomous driving. Instead,... | [
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2 | Diff-Retinex: Rethinking Low-light Image Enhancement with A Generative Diffusion Model | [
"Xunpeng Yi",
"Han Xu",
"Hao Zhang",
"Linfeng Tang",
"Jiayi Ma"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yi_Diff-Retinex_Rethinking_Low-light_Image_Enhancement_with_A_Generative_Diffusion_Model_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yi_Diff-Retinex_Rethinking_Low-light_Image_Enhancement_with_A_Generative_Diffusion_Model_ICCV_2023_paper.pdf | null | 2308.13164 | title_snapshot | @InProceedings{Yi_2023_ICCV,
author = {Yi, Xunpeng and Xu, Han and Zhang, Hao and Tang, Linfeng and Ma, Jiayi},
title = {Diff-Retinex: Rethinking Low-light Image Enhancement with A Generative Diffusion Model},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)... | In this paper, we rethink the low-light image enhancement task and propose a physically explainable and generative diffusion model for low-light image enhancement, termed as Diff-Retinex. We aim to integrate the advantages of the physical model and the generative network. Furthermore, we hope to supplement and even ded... | [
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3 | Bird's-Eye-View Scene Graph for Vision-Language Navigation | [
"Rui Liu",
"Xiaohan Wang",
"Wenguan Wang",
"Yi Yang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Liu_Birds-Eye-View_Scene_Graph_for_Vision-Language_Navigation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_Birds-Eye-View_Scene_Graph_for_Vision-Language_Navigation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Liu_Birds-Eye-View_Scene_Graph_ICCV_2023_supplemental.pdf | 2308.04758 | title_snapshot | @InProceedings{Liu_2023_ICCV,
author = {Liu, Rui and Wang, Xiaohan and Wang, Wenguan and Yang, Yi},
title = {Bird's-Eye-View Scene Graph for Vision-Language Navigation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year ... | Vision-language navigation (VLN), which entails an agent to navigate 3D environments following human instructions, has shown great advances. However, current agents are built upon panoramic observations, which hinders their ability to perceive 3D scene geometry and easily leads to ambiguous selection of panoramic view.... | [
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4 | PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework | [
"Bowen Li",
"Ziyuan Huang",
"Junjie Ye",
"Yiming Li",
"Sebastian Scherer",
"Hang Zhao",
"Changhong Fu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Li_PVT_A_Simple_End-to-End_Latency-Aware_Visual_Tracking_Framework_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Li_PVT_A_Simple_End-to-End_Latency-Aware_Visual_Tracking_Framework_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Li_PVT_A_Simple_ICCV_2023_supplemental.pdf | 2211.11629 | title_snapshot | @InProceedings{Li_2023_ICCV,
author = {Li, Bowen and Huang, Ziyuan and Ye, Junjie and Li, Yiming and Scherer, Sebastian and Zhao, Hang and Fu, Changhong},
title = {PVT++: A Simple End-to-End Latency-Aware Visual Tracking Framework},
booktitle = {Proceedings of the IEEE/CVF International Conference on... | Visual object tracking is essential to intelligent robots. Most existing approaches have ignored the online latency that can cause severe performance degradation during real-world processing. Especially for unmanned aerial vehicles (UAVs), where robust tracking is more challenging and onboard computation is limited, th... | [
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5 | A Dynamic Dual-Processing Object Detection Framework Inspired by the Brain's Recognition Mechanism | [
"Minying Zhang",
"Tianpeng Bu",
"Lulu Hu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhang_A_Dynamic_Dual-Processing_Object_Detection_Framework_Inspired_by_the_Brains_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_A_Dynamic_Dual-Processing_Object_Detection_Framework_Inspired_by_the_Brains_ICCV_2023_paper.pdf | null | null | null | @InProceedings{Zhang_2023_ICCV,
author = {Zhang, Minying and Bu, Tianpeng and Hu, Lulu},
title = {A Dynamic Dual-Processing Object Detection Framework Inspired by the Brain's Recognition Mechanism},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
mont... | There are two main approaches to object detection: CNN-based and Transformer-based. The former views object detection as a dense local matching problem, while the latter sees it as a sparse global retrieval problem. Research in neuroscience has shown that the recognition decision in the brain is based on two processes,... | [
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6 | Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient | [
"Zhengzhi Lu",
"He Wang",
"Ziyi Chang",
"Guoan Yang",
"Hubert P. H. Shum"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Lu_Hard_No-Box_Adversarial_Attack_on_Skeleton-Based_Human_Action_Recognition_with_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Lu_Hard_No-Box_Adversarial_Attack_on_Skeleton-Based_Human_Action_Recognition_with_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Lu_Hard_No-Box_Adversarial_ICCV_2023_supplemental.zip | 2308.05681 | cvf | @InProceedings{Lu_2023_ICCV,
author = {Lu, Zhengzhi and Wang, He and Chang, Ziyi and Yang, Guoan and Shum, Hubert P. H.},
title = {Hard No-Box Adversarial Attack on Skeleton-Based Human Action Recognition with Skeleton-Motion-Informed Gradient},
booktitle = {Proceedings of the IEEE/CVF International ... | Recently, methods for skeleton-based human activity recognition have been shown to be vulnerable to adversarial attacks. However, these attack methods require either the full knowledge of the victim (i.e. white-box attacks), access to training data (i.e. transfer-based attacks) or frequent model queries (i.e. black-box... | [
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7 | GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Driving | [
"Zhiyu Huang",
"Haochen Liu",
"Chen Lv"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Huang_GameFormer_Game-theoretic_Modeling_and_Learning_of_Transformer-based_Interactive_Prediction_and_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Huang_GameFormer_Game-theoretic_Modeling_and_Learning_of_Transformer-based_Interactive_Prediction_and_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Huang_GameFormer_Game-theoretic_Modeling_ICCV_2023_supplemental.pdf | 2303.05760 | cvf | @InProceedings{Huang_2023_ICCV,
author = {Huang, Zhiyu and Liu, Haochen and Lv, Chen},
title = {GameFormer: Game-theoretic Modeling and Learning of Transformer-based Interactive Prediction and Planning for Autonomous Driving},
booktitle = {Proceedings of the IEEE/CVF International Conference on Compu... | Autonomous vehicles operating in complex real-world environments require accurate predictions of interactive behaviors between traffic participants. This paper tackles the interaction prediction problem by formulating it with hierarchical game theory and proposing the GameFormer model for its implementation. The model ... | [
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8 | Towards Better Robustness against Common Corruptions for Unsupervised Domain Adaptation | [
"Zhiqiang Gao",
"Kaizhu Huang",
"Rui Zhang",
"Dawei Liu",
"Jieming Ma"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Gao_Towards_Better_Robustness_against_Common_Corruptions_for_Unsupervised_Domain_Adaptation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Gao_Towards_Better_Robustness_against_Common_Corruptions_for_Unsupervised_Domain_Adaptation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Gao_Towards_Better_Robustness_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Gao_2023_ICCV,
author = {Gao, Zhiqiang and Huang, Kaizhu and Zhang, Rui and Liu, Dawei and Ma, Jieming},
title = {Towards Better Robustness against Common Corruptions for Unsupervised Domain Adaptation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Visi... | Recent studies have investigated how to achieve robustness for unsupervised domain adaptation (UDA). While most efforts focus on adversarial robustness, i.e. how the model performs against unseen malicious adversarial perturbations, robustness against benign common corruption (RaCC) surprisingly remains under-explored ... | [
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9 | Learning in Imperfect Environment: Multi-Label Classification with Long-Tailed Distribution and Partial Labels | [
"Wenqiao Zhang",
"Changshuo Liu",
"Lingze Zeng",
"Bengchin Ooi",
"Siliang Tang",
"Yueting Zhuang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhang_Learning_in_Imperfect_Environment_Multi-Label_Classification_with_Long-Tailed_Distribution_and_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_Learning_in_Imperfect_Environment_Multi-Label_Classification_with_Long-Tailed_Distribution_and_ICCV_2023_paper.pdf | null | 2304.10539 | cvf | @InProceedings{Zhang_2023_ICCV,
author = {Zhang, Wenqiao and Liu, Changshuo and Zeng, Lingze and Ooi, Bengchin and Tang, Siliang and Zhuang, Yueting},
title = {Learning in Imperfect Environment: Multi-Label Classification with Long-Tailed Distribution and Partial Labels},
booktitle = {Proceedings of ... | Conventional multi-label classification (MLC) methods assume that all samples are fully labeled and identically distributed. Unfortunately, this assumption is unrealistic in large-scale MLC data
that has long-tailed (LT) distribution and partial labels (PL).
To address the problem, we introduce a novel task, Partial... | [
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10 | Flexible Visual Recognition by Evidential Modeling of Confusion and Ignorance | [
"Lei Fan",
"Bo Liu",
"Haoxiang Li",
"Ying Wu",
"Gang Hua"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Fan_Flexible_Visual_Recognition_by_Evidential_Modeling_of_Confusion_and_Ignorance_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Fan_Flexible_Visual_Recognition_by_Evidential_Modeling_of_Confusion_and_Ignorance_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Fan_Flexible_Visual_Recognition_ICCV_2023_supplemental.pdf | 2309.07403 | cvf | @InProceedings{Fan_2023_ICCV,
author = {Fan, Lei and Liu, Bo and Li, Haoxiang and Wu, Ying and Hua, Gang},
title = {Flexible Visual Recognition by Evidential Modeling of Confusion and Ignorance},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | In real-world scenarios, typical visual recognition systems could fail under two major causes, i.e., the misclassification between known classes and the excusable misbehavior on unknown-class images. To tackle these deficiencies, flexible visual recognition should dynamically predict multiple classes when they are unco... | [
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11 | Texture Generation on 3D Meshes with Point-UV Diffusion | [
"Xin Yu",
"Peng Dai",
"Wenbo Li",
"Lan Ma",
"Zhengzhe Liu",
"Xiaojuan Qi"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yu_Texture_Generation_on_3D_Meshes_with_Point-UV_Diffusion_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yu_Texture_Generation_on_3D_Meshes_with_Point-UV_Diffusion_ICCV_2023_paper.pdf | null | 2308.10490 | cvf | @InProceedings{Yu_2023_ICCV,
author = {Yu, Xin and Dai, Peng and Li, Wenbo and Ma, Lan and Liu, Zhengzhe and Qi, Xiaojuan},
title = {Texture Generation on 3D Meshes with Point-UV Diffusion},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = ... | In this work, we focus on synthesizing high-quality textures on 3D meshes. We present Point-UV diffusion, a coarse-to-fine pipeline that marries the denoising diffusion model with UV mapping to generate 3D consistent and high-quality texture images in UV space. We start with introducing a point diffusion model to synth... | [
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12 | Supervised Homography Learning with Realistic Dataset Generation | [
"Hai Jiang",
"Haipeng Li",
"Songchen Han",
"Haoqiang Fan",
"Bing Zeng",
"Shuaicheng Liu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Jiang_Supervised_Homography_Learning_with_Realistic_Dataset_Generation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Jiang_Supervised_Homography_Learning_with_Realistic_Dataset_Generation_ICCV_2023_paper.pdf | null | 2307.15353 | cvf | @InProceedings{Jiang_2023_ICCV,
author = {Jiang, Hai and Li, Haipeng and Han, Songchen and Fan, Haoqiang and Zeng, Bing and Liu, Shuaicheng},
title = {Supervised Homography Learning with Realistic Dataset Generation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Visio... | In this paper, we propose an iterative framework, which consists of two phases: a generation phase and a training phase, to generate realistic training data and yield a supervised homography network. In the generation phase, given an unlabeled image pair, we utilize the pre-estimated dominant plane masks and homography... | [
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13 | E2E-LOAD: End-to-End Long-form Online Action Detection | [
"Shuqiang Cao",
"Weixin Luo",
"Bairui Wang",
"Wei Zhang",
"Lin Ma"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Cao_E2E-LOAD_End-to-End_Long-form_Online_Action_Detection_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Cao_E2E-LOAD_End-to-End_Long-form_Online_Action_Detection_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Cao_E2E-LOAD_End-to-End_Long-form_ICCV_2023_supplemental.pdf | 2306.07703 | title_snapshot | @InProceedings{Cao_2023_ICCV,
author = {Cao, Shuqiang and Luo, Weixin and Wang, Bairui and Zhang, Wei and Ma, Lin},
title = {E2E-LOAD: End-to-End Long-form Online Action Detection},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October}... | Recently, feature-based methods for Online Action Detection (OAD) have been gaining traction. However, these methods are constrained by their fixed backbone design, which fails to leverage the potential benefits of a trainable backbone. This paper introduces an end-to-end learning network that revises these approaches,... | [
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14 | TALL: Thumbnail Layout for Deepfake Video Detection | [
"Yuting Xu",
"Jian Liang",
"Gengyun Jia",
"Ziming Yang",
"Yanhao Zhang",
"Ran He"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Xu_TALL_Thumbnail_Layout_for_Deepfake_Video_Detection_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Xu_TALL_Thumbnail_Layout_for_Deepfake_Video_Detection_ICCV_2023_paper.pdf | null | 2307.07494 | cvf | @InProceedings{Xu_2023_ICCV,
author = {Xu, Yuting and Liang, Jian and Jia, Gengyun and Yang, Ziming and Zhang, Yanhao and He, Ran},
title = {TALL: Thumbnail Layout for Deepfake Video Detection},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | The growing threats of deepfakes to society and cybersecurity have raised enormous public concerns, and increasing efforts have been devoted to this critical topic of deepfake video detection. Existing video methods achieve good performance but are computationally intensive. This paper introduces a simple yet effective... | [
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15 | Enhanced Soft Label for Semi-Supervised Semantic Segmentation | [
"Jie Ma",
"Chuan Wang",
"Yang Liu",
"Liang Lin",
"Guanbin Li"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Ma_Enhanced_Soft_Label_for_Semi-Supervised_Semantic_Segmentation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Ma_Enhanced_Soft_Label_for_Semi-Supervised_Semantic_Segmentation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Ma_Enhanced_Soft_Label_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Ma_2023_ICCV,
author = {Ma, Jie and Wang, Chuan and Liu, Yang and Lin, Liang and Li, Guanbin},
title = {Enhanced Soft Label for Semi-Supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October... | As a mainstream framework in the field of semi-supervised learning (SSL), self-training via pseudo labeling and its variants have witnessed impressive progress in semi-supervised semantic segmentation with the recent advance of deep neural networks. However, modern self-training based SSL algorithms use a pre-defined c... | [
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16 | Self-supervised Monocular Depth Estimation: Let's Talk About The Weather | [
"Kieran Saunders",
"George Vogiatzis",
"Luis J. Manso"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Saunders_Self-supervised_Monocular_Depth_Estimation_Lets_Talk_About_The_Weather_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Saunders_Self-supervised_Monocular_Depth_Estimation_Lets_Talk_About_The_Weather_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Saunders_Self-supervised_Monocular_Depth_ICCV_2023_supplemental.pdf | 2307.08357 | title_snapshot | @InProceedings{Saunders_2023_ICCV,
author = {Saunders, Kieran and Vogiatzis, George and Manso, Luis J.},
title = {Self-supervised Monocular Depth Estimation: Let's Talk About The Weather},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {O... | Current, self-supervised depth estimation architectures rely on clear and sunny weather scenes to train deep neural networks. However, in many locations, this assumption is too strong. For example in the UK (2021), 149 days consisted of rain. For these architectures to be effective in real-world applications, we must c... | [
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17 | Bidirectional Alignment for Domain Adaptive Detection with Transformers | [
"Liqiang He",
"Wei Wang",
"Albert Chen",
"Min Sun",
"Cheng-Hao Kuo",
"Sinisa Todorovic"
] | https://openaccess.thecvf.com/content/ICCV2023/html/He_Bidirectional_Alignment_for_Domain_Adaptive_Detection_with_Transformers_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/He_Bidirectional_Alignment_for_Domain_Adaptive_Detection_with_Transformers_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/He_Bidirectional_Alignment_for_Domain_Adaptive_Detection_with_Transformers_ICCV_2023_supplemental.pdf | null | null | @InProceedings{He_2023_ICCV,
author = {He, Liqiang and Wang, Wei and Chen, Albert and Sun, Min and Kuo, Cheng-Hao and Todorovic, Sinisa},
title = {Bidirectional Alignment for Domain Adaptive Detection with Transformers},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vi... | We propose a Bidirectional Alignment for domain adaptive Detection with Transformers (BiADT) to improve cross domain object detection performance. Existing adversarial learning based methods use gradient reverse layer (GRL) to reduce the domain gap between the source and target domains in feature representations. Since... | [
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18 | Fast Neural Scene Flow | [
"Xueqian Li",
"Jianqiao Zheng",
"Francesco Ferroni",
"Jhony Kaesemodel Pontes",
"Simon Lucey"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Li_Fast_Neural_Scene_Flow_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Li_Fast_Neural_Scene_Flow_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Li_Fast_Neural_Scene_ICCV_2023_supplemental.pdf | 2304.09121 | cvf | @InProceedings{Li_2023_ICCV,
author = {Li, Xueqian and Zheng, Jianqiao and Ferroni, Francesco and Pontes, Jhony Kaesemodel and Lucey, Simon},
title = {Fast Neural Scene Flow},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
... | Neural Scene Flow Prior (NSFP) is of significant interest to the vision community due to its inherent robustness to out-of-distribution (OOD) effects and its ability to deal with dense lidar points. The approach utilizes a coordinate neural network to estimate scene flow at runtime, without any training. However, it is... | [
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19 | CAME: Contrastive Automated Model Evaluation | [
"Ru Peng",
"Qiuyang Duan",
"Haobo Wang",
"Jiachen Ma",
"Yanbo Jiang",
"Yongjun Tu",
"Xiu Jiang",
"Junbo Zhao"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Peng_CAME_Contrastive_Automated_Model_Evaluation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Peng_CAME_Contrastive_Automated_Model_Evaluation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Peng_CAME_Contrastive_Automated_ICCV_2023_supplemental.pdf | 2308.11111 | cvf | @InProceedings{Peng_2023_ICCV,
author = {Peng, Ru and Duan, Qiuyang and Wang, Haobo and Ma, Jiachen and Jiang, Yanbo and Tu, Yongjun and Jiang, Xiu and Zhao, Junbo},
title = {CAME: Contrastive Automated Model Evaluation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer V... | The Automated Model Evaluation (AutoEval) framework entertains the possibility of evaluating a trained machine learning model without resorting to a labeled testing set.
Despite the promise and some decent results, the existing AutoEval methods heavily rely on computing distribution shifts between the unlabelled testi... | [
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20 | ExposureDiffusion: Learning to Expose for Low-light Image Enhancement | [
"Yufei Wang",
"Yi Yu",
"Wenhan Yang",
"Lanqing Guo",
"Lap-Pui Chau",
"Alex C. Kot",
"Bihan Wen"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Wang_ExposureDiffusion_Learning_to_Expose_for_Low-light_Image_Enhancement_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Wang_ExposureDiffusion_Learning_to_Expose_for_Low-light_Image_Enhancement_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Wang_ExposureDiffusion_Learning_to_ICCV_2023_supplemental.pdf | 2307.07710 | cvf | @InProceedings{Wang_2023_ICCV,
author = {Wang, Yufei and Yu, Yi and Yang, Wenhan and Guo, Lanqing and Chau, Lap-Pui and Kot, Alex C. and Wen, Bihan},
title = {ExposureDiffusion: Learning to Expose for Low-light Image Enhancement},
booktitle = {Proceedings of the IEEE/CVF International Conference on C... | Previous raw image-based low-light image enhancement methods predominantly relied on feed-forward neural networks to learn deterministic mappings from low-light to normally-exposed images. However, they failed to capture critical distribution information, leading to visually undesirable results. This work addresses the... | [
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21 | HM-ViT: Hetero-Modal Vehicle-to-Vehicle Cooperative Perception with Vision Transformer | [
"Hao Xiang",
"Runsheng Xu",
"Jiaqi Ma"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Xiang_HM-ViT_Hetero-Modal_Vehicle-to-Vehicle_Cooperative_Perception_with_Vision_Transformer_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Xiang_HM-ViT_Hetero-Modal_Vehicle-to-Vehicle_Cooperative_Perception_with_Vision_Transformer_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Xiang_HM-ViT_Hetero-Modal_Vehicle-to-Vehicle_ICCV_2023_supplemental.zip | 2304.10628 | title_snapshot | @InProceedings{Xiang_2023_ICCV,
author = {Xiang, Hao and Xu, Runsheng and Ma, Jiaqi},
title = {HM-ViT: Hetero-Modal Vehicle-to-Vehicle Cooperative Perception with Vision Transformer},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {Octobe... | Vehicle-to-Vehicle technologies have enabled autonomous vehicles to share information to see through occlusions, greatly enhancing perception performance. Nevertheless, existing works all focused on homogeneous traffic where vehicles are equipped with the same type of sensors, which significantly hampers the scale of c... | [
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22 | HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces | [
"Stella Bounareli",
"Christos Tzelepis",
"Vasileios Argyriou",
"Ioannis Patras",
"Georgios Tzimiropoulos"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Bounareli_HyperReenact_One-Shot_Reenactment_via_Jointly_Learning_to_Refine_and_Retarget_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Bounareli_HyperReenact_One-Shot_Reenactment_via_Jointly_Learning_to_Refine_and_Retarget_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Bounareli_HyperReenact_One-Shot_Reenactment_ICCV_2023_supplemental.zip | 2307.10797 | cvf | @InProceedings{Bounareli_2023_ICCV,
author = {Bounareli, Stella and Tzelepis, Christos and Argyriou, Vasileios and Patras, Ioannis and Tzimiropoulos, Georgios},
title = {HyperReenact: One-Shot Reenactment via Jointly Learning to Refine and Retarget Faces},
booktitle = {Proceedings of the IEEE/CVF Int... | In this paper, we present our method for neural face reenactment, called HyperReenact, that aims to generate realistic talking head images of a source identity, driven by a target facial pose. Existing state-of-the-art face reenactment methods train controllable generative models that learn to synthesize realistic faci... | [
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23 | Order-preserving Consistency Regularization for Domain Adaptation and Generalization | [
"Mengmeng Jing",
"Xiantong Zhen",
"Jingjing Li",
"Cees G. M. Snoek"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Jing_Order-preserving_Consistency_Regularization_for_Domain_Adaptation_and_Generalization_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Jing_Order-preserving_Consistency_Regularization_for_Domain_Adaptation_and_Generalization_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Jing_Order-preserving_Consistency_Regularization_ICCV_2023_supplemental.pdf | 2309.13258 | cvf | @InProceedings{Jing_2023_ICCV,
author = {Jing, Mengmeng and Zhen, Xiantong and Li, Jingjing and Snoek, Cees G. M.},
title = {Order-preserving Consistency Regularization for Domain Adaptation and Generalization},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICC... | Deep learning models fail on cross-domain challenges if the model is oversensitive to domain-specific attributes, e.g., lightning, background, camera angle, etc. To alleviate this problem, data augmentation coupled with consistency regularization are commonly adopted to make the model less sensitive to domain-specific ... | [
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24 | RefEgo: Referring Expression Comprehension Dataset from First-Person Perception of Ego4D | [
"Shuhei Kurita",
"Naoki Katsura",
"Eri Onami"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Kurita_RefEgo_Referring_Expression_Comprehension_Dataset_from_First-Person_Perception_of_Ego4D_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Kurita_RefEgo_Referring_Expression_Comprehension_Dataset_from_First-Person_Perception_of_Ego4D_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Kurita_RefEgo_Referring_Expression_ICCV_2023_supplemental.pdf | 2308.12035 | cvf | @InProceedings{Kurita_2023_ICCV,
author = {Kurita, Shuhei and Katsura, Naoki and Onami, Eri},
title = {RefEgo: Referring Expression Comprehension Dataset from First-Person Perception of Ego4D},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | Grounding textual expressions on scene objects from first-person views is a truly demanding capability in developing agents that are aware of their surroundings and behave following intuitive text instructions. Such capability is of necessity for glass-devices or autonomous robots to localize referred objects in the re... | [
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25 | Exploring Temporal Frequency Spectrum in Deep Video Deblurring | [
"Qi Zhu",
"Man Zhou",
"Naishan Zheng",
"Chongyi Li",
"Jie Huang",
"Feng Zhao"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhu_Exploring_Temporal_Frequency_Spectrum_in_Deep_Video_Deblurring_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhu_Exploring_Temporal_Frequency_Spectrum_in_Deep_Video_Deblurring_ICCV_2023_paper.pdf | null | null | null | @InProceedings{Zhu_2023_ICCV,
author = {Zhu, Qi and Zhou, Man and Zheng, Naishan and Li, Chongyi and Huang, Jie and Zhao, Feng},
title = {Exploring Temporal Frequency Spectrum in Deep Video Deblurring},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Video deblurring aims to restore the latent video frames from their blurred counterparts. Despite the remarkable progress, most promising video deblurring methods only investigate the temporal priors in the spatial domain and rarely explore their its potential in the frequency domain. In this paper, we revisit the blur... | [
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26 | Unified Visual Relationship Detection with Vision and Language Models | [
"Long Zhao",
"Liangzhe Yuan",
"Boqing Gong",
"Yin Cui",
"Florian Schroff",
"Ming-Hsuan Yang",
"Hartwig Adam",
"Ting Liu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhao_Unified_Visual_Relationship_Detection_with_Vision_and_Language_Models_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_Unified_Visual_Relationship_Detection_with_Vision_and_Language_Models_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhao_Unified_Visual_Relationship_Detection_with_Vision_and_Language_Models_ICCV_2023_supplemental.pdf | 2303.08998 | cvf | @InProceedings{Zhao_2023_ICCV,
author = {Zhao, Long and Yuan, Liangzhe and Gong, Boqing and Cui, Yin and Schroff, Florian and Yang, Ming-Hsuan and Adam, Hartwig and Liu, Ting},
title = {Unified Visual Relationship Detection with Vision and Language Models},
booktitle = {Proceedings of the IEEE/CVF In... | This work focuses on training a single visual relationship detector predicting over the union of label spaces from multiple datasets. Merging labels spanning different datasets could be challenging due to inconsistent taxonomies. The issue is exacerbated in visual relationship detection when second-order visual semanti... | [
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27 | Occ^2Net: Robust Image Matching Based on 3D Occupancy Estimation for Occluded Regions | [
"Miao Fan",
"Mingrui Chen",
"Chen Hu",
"Shuchang Zhou"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Fan_Occ2Net_Robust_Image_Matching_Based_on_3D_Occupancy_Estimation_for_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Fan_Occ2Net_Robust_Image_Matching_Based_on_3D_Occupancy_Estimation_for_ICCV_2023_paper.pdf | null | 2308.16160 | title_judge | @InProceedings{Fan_2023_ICCV,
author = {Fan, Miao and Chen, Mingrui and Hu, Chen and Zhou, Shuchang},
title = {Occ{\textasciicircum}2Net: Robust Image Matching Based on 3D Occupancy Estimation for Occluded Regions},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision ... | Image matching is a fundamental and critical task in various visual applications, such as Simultaneous Localization and Mapping (SLAM) and image retrieval, which require accurate pose estimation. However, most existing methods ignore the occlusion relations between objects caused by camera motion and scene structure.
... | [
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28 | Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation | [
"Samaneh Azadi",
"Akbar Shah",
"Thomas Hayes",
"Devi Parikh",
"Sonal Gupta"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Azadi_Make-An-Animation_Large-Scale_Text-conditional_3D_Human_Motion_Generation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Azadi_Make-An-Animation_Large-Scale_Text-conditional_3D_Human_Motion_Generation_ICCV_2023_paper.pdf | null | 2305.09662 | title_snapshot | @InProceedings{Azadi_2023_ICCV,
author = {Azadi, Samaneh and Shah, Akbar and Hayes, Thomas and Parikh, Devi and Gupta, Sonal},
title = {Make-An-Animation: Large-Scale Text-conditional 3D Human Motion Generation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (IC... | Text-guided human motion generation has drawn significant interest because of its impactful applications spanning animation and robotics. Recently, application of diffusion models for motion generation has enabled improvements in the quality of generated motions. However, existing approaches are limited by their relian... | [
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29 | Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis | [
"Lukas Struppek",
"Dominik Hintersdorf",
"Kristian Kersting"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Struppek_Rickrolling_the_Artist_Injecting_Backdoors_into_Text_Encoders_for_Text-to-Image_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Struppek_Rickrolling_the_Artist_Injecting_Backdoors_into_Text_Encoders_for_Text-to-Image_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Struppek_Rickrolling_the_Artist_ICCV_2023_supplemental.pdf | 2211.02408 | cvf | @InProceedings{Struppek_2023_ICCV,
author = {Struppek, Lukas and Hintersdorf, Dominik and Kersting, Kristian},
title = {Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (IC... | While text-to-image synthesis currently enjoys great popularity among researchers and the general public, the security of these models has been neglected so far. Many text-guided image generation models rely on pre-trained text encoders from external sources, and their users trust that the retrieved models will behave ... | [
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30 | LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation | [
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"Bharat Singh",
"Pallabi Ghosh",
"Behjat Siddiquie",
"David Jacobs"
] | https://openaccess.thecvf.com/content/ICCV2023/html/PNVR_LD-ZNet_A_Latent_Diffusion_Approach_for_Text-Based_Image_Segmentation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/PNVR_LD-ZNet_A_Latent_Diffusion_Approach_for_Text-Based_Image_Segmentation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/PNVR_LD-ZNet_A_Latent_ICCV_2023_supplemental.pdf | 2303.12343 | title_snapshot | @InProceedings{PNVR_2023_ICCV,
author = {PNVR, Koutilya and Singh, Bharat and Ghosh, Pallabi and Siddiquie, Behjat and Jacobs, David},
title = {LD-ZNet: A Latent Diffusion Approach for Text-Based Image Segmentation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision... | Large-scale pre-training tasks like image classification, captioning, or self-supervised techniques do not incentivize learning the semantic boundaries of objects. However, recent generative foundation models built using text-based latent diffusion techniques may learn semantic boundaries. This is because they have to ... | [
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31 | Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization | [
"Rui Chen",
"Qiyu Wan",
"Pavana Prakash",
"Lan Zhang",
"Xu Yuan",
"Yanmin Gong",
"Xin Fu",
"Miao Pan"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Chen_Workie-Talkie_Accelerating_Federated_Learning_by_Overlapping_Computing_and_Communications_via_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Chen_Workie-Talkie_Accelerating_Federated_Learning_by_Overlapping_Computing_and_Communications_via_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Chen_Workie-Talkie_Accelerating_Federated_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Chen_2023_ICCV,
author = {Chen, Rui and Wan, Qiyu and Prakash, Pavana and Zhang, Lan and Yuan, Xu and Gong, Yanmin and Fu, Xin and Pan, Miao},
title = {Workie-Talkie: Accelerating Federated Learning by Overlapping Computing and Communications via Contrastive Regularization},
booktitle ... | Federated learning (FL) over mobile devices is a promising distributed learning paradigm for various mobile applications. However, practical deployment of FL over mobile devices is very challenging because (i) conventional FL incurs huge training latency for mobile devices due to interleaved local computing and communi... | [
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32 | Downstream-agnostic Adversarial Examples | [
"Ziqi Zhou",
"Shengshan Hu",
"Ruizhi Zhao",
"Qian Wang",
"Leo Yu Zhang",
"Junhui Hou",
"Hai Jin"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhou_Downstream-agnostic_Adversarial_Examples_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhou_Downstream-agnostic_Adversarial_Examples_ICCV_2023_paper.pdf | null | 2307.12280 | cvf | @InProceedings{Zhou_2023_ICCV,
author = {Zhou, Ziqi and Hu, Shengshan and Zhao, Ruizhi and Wang, Qian and Zhang, Leo Yu and Hou, Junhui and Jin, Hai},
title = {Downstream-agnostic Adversarial Examples},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Self-supervised learning usually uses a large amount of unlabeled data to pre-train an encoder which can be used as a general-purpose feature extractor, such that downstream users only need to perform fine-tuning operations to enjoy the benefit of "big model". Despite this promising prospect, the security of pre-traine... | [
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33 | Late Stopping: Avoiding Confidently Learning from Mislabeled Examples | [
"Suqin Yuan",
"Lei Feng",
"Tongliang Liu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yuan_Late_Stopping_Avoiding_Confidently_Learning_from_Mislabeled_Examples_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yuan_Late_Stopping_Avoiding_Confidently_Learning_from_Mislabeled_Examples_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Yuan_Late_Stopping_Avoiding_ICCV_2023_supplemental.zip | 2308.13862 | cvf | @InProceedings{Yuan_2023_ICCV,
author = {Yuan, Suqin and Feng, Lei and Liu, Tongliang},
title = {Late Stopping: Avoiding Confidently Learning from Mislabeled Examples},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year ... | Sample selection is a prevalent method in learning with noisy labels, where small-loss data are typically considered as correctly labeled data. However, this method may not effectively identify clean hard examples with large losses, which are critical for achieving the model's closeto-optimal generalization performance... | [
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34 | AerialVLN: Vision-and-Language Navigation for UAVs | [
"Shubo Liu",
"Hongsheng Zhang",
"Yuankai Qi",
"Peng Wang",
"Yanning Zhang",
"Qi Wu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Liu_AerialVLN_Vision-and-Language_Navigation_for_UAVs_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_AerialVLN_Vision-and-Language_Navigation_for_UAVs_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Liu_AerialVLN_Vision-and-Language_Navigation_ICCV_2023_supplemental.pdf | 2308.06735 | cvf | @InProceedings{Liu_2023_ICCV,
author = {Liu, Shubo and Zhang, Hongsheng and Qi, Yuankai and Wang, Peng and Zhang, Yanning and Wu, Qi},
title = {AerialVLN: Vision-and-Language Navigation for UAVs},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | Recently emerged Vision-and-Language Navigation(VLN) tasks have drawn significant attention in both computer vision and natural language processing communities. Existing VLN tasks are built for agents that navigate on the ground, either indoors or outdoors. However, many tasks require intelligent agents to carry out in... | [
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35 | On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion | [
"Yushu Li",
"Xun Xu",
"Yongyi Su",
"Kui Jia"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Li_On_the_Robustness_of_Open-World_Test-Time_Training_Self-Training_with_Dynamic_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Li_On_the_Robustness_of_Open-World_Test-Time_Training_Self-Training_with_Dynamic_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Li_On_the_Robustness_ICCV_2023_supplemental.pdf | 2308.09942 | cvf | @InProceedings{Li_2023_ICCV,
author = {Li, Yushu and Xu, Xun and Su, Yongyi and Jia, Kui},
title = {On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
mo... | Generalizing deep learning models to unknown target domain distribution with low latency has motivated research into test-time training/adaptation (TTT/TTA). Existing approaches often focus on improving test-time training performance under well-curated target domain data. As figured out in this work, many state-of-the-... | [
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36 | Studying How to Efficiently and Effectively Guide Models with Explanations | [
"Sukrut Rao",
"Moritz Böhle",
"Amin Parchami-Araghi",
"Bernt Schiele"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Rao_Studying_How_to_Efficiently_and_Effectively_Guide_Models_with_Explanations_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Rao_Studying_How_to_Efficiently_and_Effectively_Guide_Models_with_Explanations_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Rao_Studying_How_to_ICCV_2023_supplemental.pdf | 2303.11932 | title_snapshot | @InProceedings{Rao_2023_ICCV,
author = {Rao, Sukrut and B\"ohle, Moritz and Parchami-Araghi, Amin and Schiele, Bernt},
title = {Studying How to Efficiently and Effectively Guide Models with Explanations},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Despite being highly performant, deep neural networks might base their decisions on features that spuriously correlate with the provided labels, thus hurting generalization. To mitigate this, 'model guidance' has recently gained popularity, i.e. the idea of regularizing the models' explanations to ensure that they are ... | [
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37 | Most Important Person-Guided Dual-Branch Cross-Patch Attention for Group Affect Recognition | [
"Hongxia Xie",
"Ming-Xian Lee",
"Tzu-Jui Chen",
"Hung-Jen Chen",
"Hou-I Liu",
"Hong-Han Shuai",
"Wen-Huang Cheng"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Xie_Most_Important_Person-Guided_Dual-Branch_Cross-Patch_Attention_for_Group_Affect_Recognition_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Xie_Most_Important_Person-Guided_Dual-Branch_Cross-Patch_Attention_for_Group_Affect_Recognition_ICCV_2023_paper.pdf | null | 2212.07055 | title_snapshot | @InProceedings{Xie_2023_ICCV,
author = {Xie, Hongxia and Lee, Ming-Xian and Chen, Tzu-Jui and Chen, Hung-Jen and Liu, Hou-I and Shuai, Hong-Han and Cheng, Wen-Huang},
title = {Most Important Person-Guided Dual-Branch Cross-Patch Attention for Group Affect Recognition},
booktitle = {Proceedings of the... | Group affect refers to the subjective emotion that is evoked by an external stimulus in a group, which is an important factor that shapes group behavior and outcomes. Recognizing group affect involves identifying important individuals and salient objects among a crowd that can evoke emotions. However, most existing met... | [
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38 | SkeletonMAE: Graph-based Masked Autoencoder for Skeleton Sequence Pre-training | [
"Hong Yan",
"Yang Liu",
"Yushen Wei",
"Zhen Li",
"Guanbin Li",
"Liang Lin"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yan_SkeletonMAE_Graph-based_Masked_Autoencoder_for_Skeleton_Sequence_Pre-training_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yan_SkeletonMAE_Graph-based_Masked_Autoencoder_for_Skeleton_Sequence_Pre-training_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Yan_SkeletonMAE_Graph-based_Masked_ICCV_2023_supplemental.pdf | 2307.08476 | cvf | @InProceedings{Yan_2023_ICCV,
author = {Yan, Hong and Liu, Yang and Wei, Yushen and Li, Zhen and Li, Guanbin and Lin, Liang},
title = {SkeletonMAE: Graph-based Masked Autoencoder for Skeleton Sequence Pre-training},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision ... | Skeleton sequence representation learning has shown great advantages for action recognition due to its promising ability to model human joints and topology. However, the current methods usually require sufficient labeled data for training computationally expensive models. Moreover, these methods ignore how to utilize t... | [
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39 | Achievement-Based Training Progress Balancing for Multi-Task Learning | [
"Hayoung Yun",
"Hanjoo Cho"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yun_Achievement-Based_Training_Progress_Balancing_for_Multi-Task_Learning_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yun_Achievement-Based_Training_Progress_Balancing_for_Multi-Task_Learning_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Yun_Achievement-Based_Training_Progress_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Yun_2023_ICCV,
author = {Yun, Hayoung and Cho, Hanjoo},
title = {Achievement-Based Training Progress Balancing for Multi-Task Learning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
... | Multi-task learning faces two challenging issues: (1) the high cost of annotating labels for all tasks and (2) balancing the training progress of various tasks with different natures. To resolve the label annotation issue, we construct a large-scale "partially annotated" multi-task dataset by combining task-specific da... | [
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40 | Pose-Free Neural Radiance Fields via Implicit Pose Regularization | [
"Jiahui Zhang",
"Fangneng Zhan",
"Yingchen Yu",
"Kunhao Liu",
"Rongliang Wu",
"Xiaoqin Zhang",
"Ling Shao",
"Shijian Lu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhang_Pose-Free_Neural_Radiance_Fields_via_Implicit_Pose_Regularization_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_Pose-Free_Neural_Radiance_Fields_via_Implicit_Pose_Regularization_ICCV_2023_paper.pdf | null | 2308.15049 | cvf | @InProceedings{Zhang_2023_ICCV,
author = {Zhang, Jiahui and Zhan, Fangneng and Yu, Yingchen and Liu, Kunhao and Wu, Rongliang and Zhang, Xiaoqin and Shao, Ling and Lu, Shijian},
title = {Pose-Free Neural Radiance Fields via Implicit Pose Regularization},
booktitle = {Proceedings of the IEEE/CVF Inter... | Pose-free neural radiance fields (NeRF) aim to train NeRF with unposed multi-view images and it has achieved very impressive success in recent years. Most existing works share the pipeline of training a coarse pose estimator with rendered images at first, followed by a joint optimization of estimated poses and neural r... | [
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41 | Self-supervised Learning to Bring Dual Reversed Rolling Shutter Images Alive | [
"Wei Shang",
"Dongwei Ren",
"Chaoyu Feng",
"Xiaotao Wang",
"Lei Lei",
"Wangmeng Zuo"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Shang_Self-supervised_Learning_to_Bring_Dual_Reversed_Rolling_Shutter_Images_Alive_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Shang_Self-supervised_Learning_to_Bring_Dual_Reversed_Rolling_Shutter_Images_Alive_ICCV_2023_paper.pdf | null | 2305.19862 | cvf | @InProceedings{Shang_2023_ICCV,
author = {Shang, Wei and Ren, Dongwei and Feng, Chaoyu and Wang, Xiaotao and Lei, Lei and Zuo, Wangmeng},
title = {Self-supervised Learning to Bring Dual Reversed Rolling Shutter Images Alive},
booktitle = {Proceedings of the IEEE/CVF International Conference on Comput... | Modern consumer cameras usually employ the rolling shutter (RS) mechanism, where images are captured by scanning scenes row-by-row, yielding RS distortions for dynamic scenes. To correct RS distortions, existing methods adopt a fully supervised learning manner, where high framerate global shutter (GS) images should be ... | [
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42 | Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation | [
"Chen Liang",
"Wenguan Wang",
"Jiaxu Miao",
"Yi Yang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Liang_Logic-induced_Diagnostic_Reasoning_for_Semi-supervised_Semantic_Segmentation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Liang_Logic-induced_Diagnostic_Reasoning_for_Semi-supervised_Semantic_Segmentation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Liang_Logic-induced_Diagnostic_Reasoning_for_Semi-supervised_Semantic_Segmentation_ICCV_2023_supplemental.pdf | 2308.12595 | cvf | @InProceedings{Liang_2023_ICCV,
author = {Liang, Chen and Wang, Wenguan and Miao, Jiaxu and Yang, Yi},
title = {Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = ... | Recent advances in semi-supervised semantic segmentation have been heavily reliant on pseudo labeling to compensate for limited labeled data, disregarding the valuable relational knowledge among semantic concepts. To bridge this gap, we devise LogicDiag, a brand new neural-logic semi-supervised learning framework. Our ... | [
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43 | Self-Supervised Monocular Depth Estimation by Direction-aware Cumulative Convolution Network | [
"Wencheng Han",
"Junbo Yin",
"Jianbing Shen"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Han_Self-Supervised_Monocular_Depth_Estimation_by_Direction-aware_Cumulative_Convolution_Network_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Han_Self-Supervised_Monocular_Depth_Estimation_by_Direction-aware_Cumulative_Convolution_Network_ICCV_2023_paper.pdf | null | 2308.05605 | cvf | @InProceedings{Han_2023_ICCV,
author = {Han, Wencheng and Yin, Junbo and Shen, Jianbing},
title = {Self-Supervised Monocular Depth Estimation by Direction-aware Cumulative Convolution Network},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | Monocular depth estimation is known as an ill-posed task that objects in a 2D image usually do not contain sufficient information to predict their depth. Thus, it acts differently from other tasks (e.g., classification and segmentation) in many ways. In this paper, we find that self-supervised monocular depth estimatio... | [
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44 | Encyclopedic VQA: Visual Questions About Detailed Properties of Fine-Grained Categories | [
"Thomas Mensink",
"Jasper Uijlings",
"Lluis Castrejon",
"Arushi Goel",
"Felipe Cadar",
"Howard Zhou",
"Fei Sha",
"André Araujo",
"Vittorio Ferrari"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Mensink_Encyclopedic_VQA_Visual_Questions_About_Detailed_Properties_of_Fine-Grained_Categories_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Mensink_Encyclopedic_VQA_Visual_Questions_About_Detailed_Properties_of_Fine-Grained_Categories_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Mensink_Encyclopedic_VQA_Visual_ICCV_2023_supplemental.pdf | 2306.09224 | cvf | @InProceedings{Mensink_2023_ICCV,
author = {Mensink, Thomas and Uijlings, Jasper and Castrejon, Lluis and Goel, Arushi and Cadar, Felipe and Zhou, Howard and Sha, Fei and Araujo, Andr\'e and Ferrari, Vittorio},
title = {Encyclopedic VQA: Visual Questions About Detailed Properties of Fine-Grained Categori... | We propose Encyclopedic-VQA, a large scale visual question answering (VQA) dataset featuring visual questions about detailed properties of fine-grained categories and instances. It contains 221k unique question+answer pairs each matched with (up to) 5 images, resulting in a total of 1M VQA samples. Moreover, our datase... | [
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45 | Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View | [
"Kelu Yao",
"Jin Wang",
"Boyu Diao",
"Chao Li"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yao_Towards_Understanding_the_Generalization_of_Deepfake_Detectors_from_a_Game-Theoretical_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yao_Towards_Understanding_the_Generalization_of_Deepfake_Detectors_from_a_Game-Theoretical_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Yao_Towards_Understanding_the_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Yao_2023_ICCV,
author = {Yao, Kelu and Wang, Jin and Diao, Boyu and Li, Chao},
title = {Towards Understanding the Generalization of Deepfake Detectors from a Game-Theoretical View},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | This paper aims to explain the generalization of deepfake detectors from the novel perspective of multi-order interactions among visual concepts. Specifically, we propose three hypotheses:
1. Deepfake detectors encode multi-order interactions among visual concepts, in which the low-order interactions usually have sub... | [
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46 | Few-Shot Common Action Localization via Cross-Attentional Fusion of Context and Temporal Dynamics | [
"Juntae Lee",
"Mihir Jain",
"Sungrack Yun"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Lee_Few-Shot_Common_Action_Localization_via_Cross-Attentional_Fusion_of_Context_and_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Lee_Few-Shot_Common_Action_Localization_via_Cross-Attentional_Fusion_of_Context_and_ICCV_2023_paper.pdf | null | null | null | @InProceedings{Lee_2023_ICCV,
author = {Lee, Juntae and Jain, Mihir and Yun, Sungrack},
title = {Few-Shot Common Action Localization via Cross-Attentional Fusion of Context and Temporal Dynamics},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | The goal of this paper is to localize action instances in a long untrimmed query video using just meager trimmed support videos representing a common action whose class information is not given. In this task, it is crucial to mine reliable temporal cues representing a common action from handful support videos. In our w... | [
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47 | Physically-Plausible Illumination Distribution Estimation | [
"Egor Ershov",
"Vasily Tesalin",
"Ivan Ermakov",
"Michael S. Brown"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Ershov_Physically-Plausible_Illumination_Distribution_Estimation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Ershov_Physically-Plausible_Illumination_Distribution_Estimation_ICCV_2023_paper.pdf | null | null | null | @InProceedings{Ershov_2023_ICCV,
author = {Ershov, Egor and Tesalin, Vasily and Ermakov, Ivan and Brown, Michael S.},
title = {Physically-Plausible Illumination Distribution Estimation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {Oct... | A camera's auto-white-balance (AWB) module operates under the assumption that there is a single dominant illumination in a captured scene. AWB methods estimate an image's dominant illumination and use it as the target "white point" for correction. However, in natural scenes, there are often many light sources present. ... | [
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48 | 3DPPE: 3D Point Positional Encoding for Transformer-based Multi-Camera 3D Object Detection | [
"Changyong Shu",
"Jiajun Deng",
"Fisher Yu",
"Yifan Liu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Shu_3DPPE_3D_Point_Positional_Encoding_for_Transformer-based_Multi-Camera_3D_Object_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Shu_3DPPE_3D_Point_Positional_Encoding_for_Transformer-based_Multi-Camera_3D_Object_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Shu_3DPPE_3D_Point_ICCV_2023_supplemental.pdf | 2211.14710 | title_judge | @InProceedings{Shu_2023_ICCV,
author = {Shu, Changyong and Deng, Jiajun and Yu, Fisher and Liu, Yifan},
title = {3DPPE: 3D Point Positional Encoding for Transformer-based Multi-Camera 3D Object Detection},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Transformer-based methods have swept the benchmarks on 2D and 3D detection on images. Because tokenization before the attention mechanism drops the spatial information, positional encoding becomes critical for those methods. Recent works found that encodings based on samples of the 3D viewing rays can significantly imp... | [
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49 | Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach | [
"Qinying Liu",
"Zilei Wang",
"Shenghai Rong",
"Junjie Li",
"Yixin Zhang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Liu_Revisiting_Foreground_and_Background_Separation_in_Weakly-supervised_Temporal_Action_Localization_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_Revisiting_Foreground_and_Background_Separation_in_Weakly-supervised_Temporal_Action_Localization_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Liu_Revisiting_Foreground_and_ICCV_2023_supplemental.pdf | 2312.14138 | title_snapshot | @InProceedings{Liu_2023_ICCV,
author = {Liu, Qinying and Wang, Zilei and Rong, Shenghai and Li, Junjie and Zhang, Yixin},
title = {Revisiting Foreground and Background Separation in Weakly-supervised Temporal Action Localization: A Clustering-based Approach},
booktitle = {Proceedings of the IEEE/CVF ... | Weakly-supervised temporal action localization aims to localize action instances in videos with only video-level action labels. Existing methods mainly embrace a localization-by-classification pipeline that optimizes the snippet-level prediction with a video classification loss. However, this formulation suffers from t... | [
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50 | VertexSerum: Poisoning Graph Neural Networks for Link Inference | [
"Ruyi Ding",
"Shijin Duan",
"Xiaolin Xu",
"Yunsi Fei"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Ding_VertexSerum_Poisoning_Graph_Neural_Networks_for_Link_Inference_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Ding_VertexSerum_Poisoning_Graph_Neural_Networks_for_Link_Inference_ICCV_2023_paper.pdf | null | 2308.01469 | cvf | @InProceedings{Ding_2023_ICCV,
author = {Ding, Ruyi and Duan, Shijin and Xu, Xiaolin and Fei, Yunsi},
title = {VertexSerum: Poisoning Graph Neural Networks for Link Inference},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
... | Graph neural networks (GNNs) have brought superb performance to various applications utilizing graph structural data, such as social analysis and fraud detection. The graph links, e.g., social relationships and transaction history, are sensitive and valuable information, which raises privacy concerns when using GNNs. T... | [
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51 | NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D Object Detection | [
"Chenfeng Xu",
"Bichen Wu",
"Ji Hou",
"Sam Tsai",
"Ruilong Li",
"Jialiang Wang",
"Wei Zhan",
"Zijian He",
"Peter Vajda",
"Kurt Keutzer",
"Masayoshi Tomizuka"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Xu_NeRF-Det_Learning_Geometry-Aware_Volumetric_Representation_for_Multi-View_3D_Object_Detection_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Xu_NeRF-Det_Learning_Geometry-Aware_Volumetric_Representation_for_Multi-View_3D_Object_Detection_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Xu_NeRF-Det_Learning_Geometry-Aware_ICCV_2023_supplemental.pdf | 2307.14620 | title_snapshot | @InProceedings{Xu_2023_ICCV,
author = {Xu, Chenfeng and Wu, Bichen and Hou, Ji and Tsai, Sam and Li, Ruilong and Wang, Jialiang and Zhan, Wei and He, Zijian and Vajda, Peter and Keutzer, Kurt and Tomizuka, Masayoshi},
title = {NeRF-Det: Learning Geometry-Aware Volumetric Representation for Multi-View 3D ... | We present NeRF-Det, a novel method for indoor 3D detection with posed RGB images as input. Unlike existing indoor 3D detection methods that struggle to model scene geometry, our method makes novel use of NeRF in an end-to-end manner to explicitly estimate 3D geometry, thereby improving 3D detection performance. Specif... | [
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52 | Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perception | [
"Kun Yang",
"Dingkang Yang",
"Jingyu Zhang",
"Mingcheng Li",
"Yang Liu",
"Jing Liu",
"Hanqi Wang",
"Peng Sun",
"Liang Song"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yang_Spatio-Temporal_Domain_Awareness_for_Multi-Agent_Collaborative_Perception_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yang_Spatio-Temporal_Domain_Awareness_for_Multi-Agent_Collaborative_Perception_ICCV_2023_paper.pdf | null | 2307.13929 | cvf | @InProceedings{Yang_2023_ICCV,
author = {Yang, Kun and Yang, Dingkang and Zhang, Jingyu and Li, Mingcheng and Liu, Yang and Liu, Jing and Wang, Hanqi and Sun, Peng and Song, Liang},
title = {Spatio-Temporal Domain Awareness for Multi-Agent Collaborative Perception},
booktitle = {Proceedings of the IE... | Multi-agent collaborative perception as a potential application for vehicle-to-everything communication could significantly improve the perception performance of autonomous vehicles over single-agent perception. However, several challenges remain in achieving pragmatic information sharing in this emerging research. In ... | [
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53 | LPFF: A Portrait Dataset for Face Generators Across Large Poses | [
"Yiqian Wu",
"Jing Zhang",
"Hongbo Fu",
"Xiaogang Jin"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Wu_LPFF_A_Portrait_Dataset_for_Face_Generators_Across_Large_Poses_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Wu_LPFF_A_Portrait_Dataset_for_Face_Generators_Across_Large_Poses_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Wu_LPFF_A_Portrait_ICCV_2023_supplemental.pdf | 2303.14407 | cvf | @InProceedings{Wu_2023_ICCV,
author = {Wu, Yiqian and Zhang, Jing and Fu, Hongbo and Jin, Xiaogang},
title = {LPFF: A Portrait Dataset for Face Generators Across Large Poses},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
... | Existing face generators exhibit exceptional performance on faces in small to medium poses (with respect to frontal faces) but struggle to produce realistic results for large poses. The distorted rendering results on large poses in 3D-aware generators further show that the generated 3D face shapes are far from the dist... | [
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54 | Pseudo-label Alignment for Semi-supervised Instance Segmentation | [
"Jie Hu",
"Chen Chen",
"Liujuan Cao",
"Shengchuan Zhang",
"Annan Shu",
"Guannan Jiang",
"Rongrong Ji"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Hu_Pseudo-label_Alignment_for_Semi-supervised_Instance_Segmentation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Hu_Pseudo-label_Alignment_for_Semi-supervised_Instance_Segmentation_ICCV_2023_paper.pdf | null | 2308.05359 | cvf | @InProceedings{Hu_2023_ICCV,
author = {Hu, Jie and Chen, Chen and Cao, Liujuan and Zhang, Shengchuan and Shu, Annan and Jiang, Guannan and Ji, Rongrong},
title = {Pseudo-label Alignment for Semi-supervised Instance Segmentation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Co... | Pseudo-labeling is significant for semi-supervised instance segmentation, which generates instance masks and classes from unannotated images for subsequent training. However, in existing pipelines, pseudo-labels that contain valuable information may be directly filtered out due to mismatches in class and mask quality. ... | [
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55 | Deep Geometrized Cartoon Line Inbetweening | [
"Li Siyao",
"Tianpei Gu",
"Weiye Xiao",
"Henghui Ding",
"Ziwei Liu",
"Chen Change Loy"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Siyao_Deep_Geometrized_Cartoon_Line_Inbetweening_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Siyao_Deep_Geometrized_Cartoon_Line_Inbetweening_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Siyao_Deep_Geometrized_Cartoon_ICCV_2023_supplemental.zip | 2309.16643 | title_snapshot | @InProceedings{Siyao_2023_ICCV,
author = {Siyao, Li and Gu, Tianpei and Xiao, Weiye and Ding, Henghui and Liu, Ziwei and Loy, Chen Change},
title = {Deep Geometrized Cartoon Line Inbetweening},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | We aim to address a significant but understudied problem in the anime industry, namely the inbetweening of cartoon line drawings. Inbetweening involves generating intermediate frames between two black-and-white line drawings and is a time-consuming and expensive process that can benefit from automation. However, existi... | [
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56 | MixBag: Bag-Level Data Augmentation for Learning from Label Proportions | [
"Takanori Asanomi",
"Shinnosuke Matsuo",
"Daiki Suehiro",
"Ryoma Bise"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Asanomi_MixBag_Bag-Level_Data_Augmentation_for_Learning_from_Label_Proportions_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Asanomi_MixBag_Bag-Level_Data_Augmentation_for_Learning_from_Label_Proportions_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Asanomi_MixBag_Bag-Level_Data_ICCV_2023_supplemental.pdf | 2308.08822 | cvf | @InProceedings{Asanomi_2023_ICCV,
author = {Asanomi, Takanori and Matsuo, Shinnosuke and Suehiro, Daiki and Bise, Ryoma},
title = {MixBag: Bag-Level Data Augmentation for Learning from Label Proportions},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Learning from label proportions (LLP) is a promising weakly supervised learning problem. In LLP, a set of instances (bag) has label proportions but no instance-level labels.
LLP aims to train an instance-level classifier by using the label proportions of the bag.
In this paper, we propose a bag-level data augmentatio... | [
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57 | Effective Real Image Editing with Accelerated Iterative Diffusion Inversion | [
"Zhihong Pan",
"Riccardo Gherardi",
"Xiufeng Xie",
"Stephen Huang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Pan_Effective_Real_Image_Editing_with_Accelerated_Iterative_Diffusion_Inversion_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Pan_Effective_Real_Image_Editing_with_Accelerated_Iterative_Diffusion_Inversion_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Pan_Effective_Real_Image_ICCV_2023_supplemental.pdf | 2309.04907 | cvf | @InProceedings{Pan_2023_ICCV,
author = {Pan, Zhihong and Gherardi, Riccardo and Xie, Xiufeng and Huang, Stephen},
title = {Effective Real Image Editing with Accelerated Iterative Diffusion Inversion},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
mo... | Despite all recent progress, it is still challenging to edit and manipulate natural images with modern generative models. When using Generative Adversarial Network (GAN), one major hurdle is in the inversion process mapping a real image to its corresponding noise vector in the latent space, since its necessary to be ab... | [
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58 | 3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation | [
"Yi Zhang",
"Pengliang Ji",
"Angtian Wang",
"Jieru Mei",
"Adam Kortylewski",
"Alan Yuille"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhang_3D-Aware_Neural_Body_Fitting_for_Occlusion_Robust_3D_Human_Pose_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhang_3D-Aware_Neural_Body_Fitting_for_Occlusion_Robust_3D_Human_Pose_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhang_3D-Aware_Neural_Body_ICCV_2023_supplemental.pdf | 2308.10123 | cvf | @InProceedings{Zhang_2023_ICCV,
author = {Zhang, Yi and Ji, Pengliang and Wang, Angtian and Mei, Jieru and Kortylewski, Adam and Yuille, Alan},
title = {3D-Aware Neural Body Fitting for Occlusion Robust 3D Human Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Co... | Regression-based methods for 3D human pose estimation directly predict the 3D pose parameters from a 2D image using deep networks. While achieving state-of-the-art performance on standard benchmarks, their performance degrades under occlusion. In contrast, optimization-based methods fit a parametric body model to 2D fe... | [
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59 | Chinese Text Recognition with A Pre-Trained CLIP-Like Model Through Image-IDS Aligning | [
"Haiyang Yu",
"Xiaocong Wang",
"Bin Li",
"Xiangyang Xue"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yu_Chinese_Text_Recognition_with_A_Pre-Trained_CLIP-Like_Model_Through_Image-IDS_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yu_Chinese_Text_Recognition_with_A_Pre-Trained_CLIP-Like_Model_Through_Image-IDS_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Yu_Chinese_Text_Recognition_with_A_Pre-Trained_CLIP-Like_Model_Through_Image-IDS_ICCV_2023_supplemental.pdf | 2309.01083 | cvf | @InProceedings{Yu_2023_ICCV,
author = {Yu, Haiyang and Wang, Xiaocong and Li, Bin and Xue, Xiangyang},
title = {Chinese Text Recognition with A Pre-Trained CLIP-Like Model Through Image-IDS Aligning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
mo... | Scene text recognition has been studied for decades due to its broad applications. However, despite Chinese characters possessing different characteristics from Latin characters, such as complex inner structures and large categories, few methods have been proposed for Chinese Text Recognition (CTR). Particularly, the c... | [
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60 | MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond | [
"Yixuan Li",
"Lihan Jiang",
"Linning Xu",
"Yuanbo Xiangli",
"Zhenzhi Wang",
"Dahua Lin",
"Bo Dai"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Li_MatrixCity_A_Large-scale_City_Dataset_for_City-scale_Neural_Rendering_and_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Li_MatrixCity_A_Large-scale_City_Dataset_for_City-scale_Neural_Rendering_and_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Li_MatrixCity_A_Large-scale_ICCV_2023_supplemental.pdf | 2309.16553 | title_snapshot | @InProceedings{Li_2023_ICCV,
author = {Li, Yixuan and Jiang, Lihan and Xu, Linning and Xiangli, Yuanbo and Wang, Zhenzhi and Lin, Dahua and Dai, Bo},
title = {MatrixCity: A Large-scale City Dataset for City-scale Neural Rendering and Beyond},
booktitle = {Proceedings of the IEEE/CVF International Con... | Neural radiance fields (NeRF) and its subsequent variants have led to remarkable progress in neural rendering. While most of recent neural rendering works focus on objects and small-scale scenes, developing neural rendering methods for city-scale scenes is of great potential in many real-world applications. However, th... | [
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61 | LinkGAN: Linking GAN Latents to Pixels for Controllable Image Synthesis | [
"Jiapeng Zhu",
"Ceyuan Yang",
"Yujun Shen",
"Zifan Shi",
"Bo Dai",
"Deli Zhao",
"Qifeng Chen"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhu_LinkGAN_Linking_GAN_Latents_to_Pixels_for_Controllable_Image_Synthesis_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhu_LinkGAN_Linking_GAN_Latents_to_Pixels_for_Controllable_Image_Synthesis_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhu_LinkGAN_Linking_GAN_ICCV_2023_supplemental.pdf | 2301.04604 | cvf | @InProceedings{Zhu_2023_ICCV,
author = {Zhu, Jiapeng and Yang, Ceyuan and Shen, Yujun and Shi, Zifan and Dai, Bo and Zhao, Deli and Chen, Qifeng},
title = {LinkGAN: Linking GAN Latents to Pixels for Controllable Image Synthesis},
booktitle = {Proceedings of the IEEE/CVF International Conference on Co... | This work presents an easy-to-use regularizer for GAN training, which helps explicitly link some axes of the latent space to a set of pixels in the synthesized image. Establishing such a connection facilitates a more convenient local control of GAN generation, where users can alter the image content only within a spati... | [
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62 | Exploiting Proximity-Aware Tasks for Embodied Social Navigation | [
"Enrico Cancelli",
"Tommaso Campari",
"Luciano Serafini",
"Angel X. Chang",
"Lamberto Ballan"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Cancelli_Exploiting_Proximity-Aware_Tasks_for_Embodied_Social_Navigation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Cancelli_Exploiting_Proximity-Aware_Tasks_for_Embodied_Social_Navigation_ICCV_2023_paper.pdf | null | 2212.00767 | cvf | @InProceedings{Cancelli_2023_ICCV,
author = {Cancelli, Enrico and Campari, Tommaso and Serafini, Luciano and Chang, Angel X. and Ballan, Lamberto},
title = {Exploiting Proximity-Aware Tasks for Embodied Social Navigation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer ... | Learning how to navigate among humans in an occluded and spatially constrained indoor environment, is a key ability required to embodied agents to be integrated into our society. In this paper, we propose an end-to-end architecture that exploits Proximity-Aware Tasks (referred as to Risk and Proximity Compass) to injec... | [
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63 | SVDiff: Compact Parameter Space for Diffusion Fine-Tuning | [
"Ligong Han",
"Yinxiao Li",
"Han Zhang",
"Peyman Milanfar",
"Dimitris Metaxas",
"Feng Yang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Han_SVDiff_Compact_Parameter_Space_for_Diffusion_Fine-Tuning_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Han_SVDiff_Compact_Parameter_Space_for_Diffusion_Fine-Tuning_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Han_SVDiff_Compact_Parameter_ICCV_2023_supplemental.pdf | 2303.11305 | cvf | @InProceedings{Han_2023_ICCV,
author = {Han, Ligong and Li, Yinxiao and Zhang, Han and Milanfar, Peyman and Metaxas, Dimitris and Yang, Feng},
title = {SVDiff: Compact Parameter Space for Diffusion Fine-Tuning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICC... | Recently, diffusion models have achieved remarkable success in text-to-image generation, enabling the creation of high-quality images from text prompts and various conditions. However, existing methods for customizing these models are limited by handling multiple personalized subjects and the risk of overfitting. Moreo... | [
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64 | UniFace: Unified Cross-Entropy Loss for Deep Face Recognition | [
"Jiancan Zhou",
"Xi Jia",
"Qiufu Li",
"Linlin Shen",
"Jinming Duan"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhou_UniFace_Unified_Cross-Entropy_Loss_for_Deep_Face_Recognition_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhou_UniFace_Unified_Cross-Entropy_Loss_for_Deep_Face_Recognition_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhou_UniFace_Unified_Cross-Entropy_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Zhou_2023_ICCV,
author = {Zhou, Jiancan and Jia, Xi and Li, Qiufu and Shen, Linlin and Duan, Jinming},
title = {UniFace: Unified Cross-Entropy Loss for Deep Face Recognition},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = ... | As a widely used loss function in deep face recognition, the softmax loss cannot guarantee that the minimum positive sample-to-class similarity is larger than the maximum negative sample-to-class similarity. As a result, no unified threshold is available to separate positive sample-to-class pairs from negative sample-t... | [
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65 | Jumping through Local Minima: Quantization in the Loss Landscape of Vision Transformers | [
"Natalia Frumkin",
"Dibakar Gope",
"Diana Marculescu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Frumkin_Jumping_through_Local_Minima_Quantization_in_the_Loss_Landscape_of_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Frumkin_Jumping_through_Local_Minima_Quantization_in_the_Loss_Landscape_of_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Frumkin_Jumping_through_Local_ICCV_2023_supplemental.pdf | 2308.10814 | cvf | @InProceedings{Frumkin_2023_ICCV,
author = {Frumkin, Natalia and Gope, Dibakar and Marculescu, Diana},
title = {Jumping through Local Minima: Quantization in the Loss Landscape of Vision Transformers},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
m... | Quantization scale and bit-width are the most important parameters when considering how to quantize a neural network. Prior work focuses on optimizing quantization scales in a global manner through gradient methods (gradient descent & Hessian analysis). Yet, when applying perturbations to quantization scales, we observ... | [
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66 | Hierarchical Contrastive Learning for Pattern-Generalizable Image Corruption Detection | [
"Xin Feng",
"Yifeng Xu",
"Guangming Lu",
"Wenjie Pei"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Feng_Hierarchical_Contrastive_Learning_for_Pattern-Generalizable_Image_Corruption_Detection_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Feng_Hierarchical_Contrastive_Learning_for_Pattern-Generalizable_Image_Corruption_Detection_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Feng_Hierarchical_Contrastive_Learning_ICCV_2023_supplemental.pdf | 2308.14061 | cvf | @InProceedings{Feng_2023_ICCV,
author = {Feng, Xin and Xu, Yifeng and Lu, Guangming and Pei, Wenjie},
title = {Hierarchical Contrastive Learning for Pattern-Generalizable Image Corruption Detection},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
mon... | Effective image restoration with large-size corruptions, such as blind image inpainting, entails precise detection of corruption region masks which remains extremely challenging due to diverse shapes and patterns of corruptions. In this work, we present a novel method for automatic corruption detection, which allows fo... | [
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67 | Learning Optical Flow from Event Camera with Rendered Dataset | [
"Xinglong Luo",
"Kunming Luo",
"Ao Luo",
"Zhengning Wang",
"Ping Tan",
"Shuaicheng Liu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Luo_Learning_Optical_Flow_from_Event_Camera_with_Rendered_Dataset_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Luo_Learning_Optical_Flow_from_Event_Camera_with_Rendered_Dataset_ICCV_2023_paper.pdf | null | 2303.11011 | cvf | @InProceedings{Luo_2023_ICCV,
author = {Luo, Xinglong and Luo, Kunming and Luo, Ao and Wang, Zhengning and Tan, Ping and Liu, Shuaicheng},
title = {Learning Optical Flow from Event Camera with Rendered Dataset},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICC... | We study the problem of estimating optical flow from event cameras. One important issue is how to build a high-quality event-flow dataset with accurate event values and flow labels. Previous datasets are created by either capturing real scenes by event cameras or synthesizing from images with pasted foreground objects.... | [
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68 | EPiC: Ensemble of Partial Point Clouds for Robust Classification | [
"Meir Yossef Levi",
"Guy Gilboa"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Levi_EPiC_Ensemble_of_Partial_Point_Clouds_for_Robust_Classification_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Levi_EPiC_Ensemble_of_Partial_Point_Clouds_for_Robust_Classification_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Levi_EPiC_Ensemble_of_ICCV_2023_supplemental.pdf | 2303.11419 | cvf | @InProceedings{Levi_2023_ICCV,
author = {Levi, Meir Yossef and Gilboa, Guy},
title = {EPiC: Ensemble of Partial Point Clouds for Robust Classification},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
... | Robust point cloud classification is crucial for real-world applications,as consumer-type 3D sensors often yield partial and noisy data, degraded by various artifacts. In this work we propose a general ensemble framework, based on partial point cloud sampling. Each ensemble member is exposed to only partial input data.... | [
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69 | Distilling Large Vision-Language Model with Out-of-Distribution Generalizability | [
"Xuanlin Li",
"Yunhao Fang",
"Minghua Liu",
"Zhan Ling",
"Zhuowen Tu",
"Hao Su"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Li_Distilling_Large_Vision-Language_Model_with_Out-of-Distribution_Generalizability_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Li_Distilling_Large_Vision-Language_Model_with_Out-of-Distribution_Generalizability_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Li_Distilling_Large_Vision-Language_ICCV_2023_supplemental.pdf | 2307.03135 | cvf | @InProceedings{Li_2023_ICCV,
author = {Li, Xuanlin and Fang, Yunhao and Liu, Minghua and Ling, Zhan and Tu, Zhuowen and Su, Hao},
title = {Distilling Large Vision-Language Model with Out-of-Distribution Generalizability},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer V... | Large vision-language models have achieved outstanding performance, but their size and computational requirements make their deployment on resource-constrained devices and time-sensitive tasks impractical. Model distillation, the process of creating smaller, faster models that maintain the performance of larger models,... | [
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70 | Cross-Modal Learning with 3D Deformable Attention for Action Recognition | [
"Sangwon Kim",
"Dasom Ahn",
"Byoung Chul Ko"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Kim_Cross-Modal_Learning_with_3D_Deformable_Attention_for_Action_Recognition_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Kim_Cross-Modal_Learning_with_3D_Deformable_Attention_for_Action_Recognition_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Kim_Cross-Modal_Learning_with_ICCV_2023_supplemental.pdf | 2212.05638 | cvf | @InProceedings{Kim_2023_ICCV,
author = {Kim, Sangwon and Ahn, Dasom and Ko, Byoung Chul},
title = {Cross-Modal Learning with 3D Deformable Attention for Action Recognition},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
ye... | An important challenge in vision-based action recognition is the embedding of spatiotemporal features with two or more heterogeneous modalities into a single feature. In this study, we propose a new 3D deformable transformer for action recognition with adaptive spatiotemporal receptive fields and a cross-modal learning... | [
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71 | What do neural networks learn in image classification? A frequency shortcut perspective | [
"Shunxin Wang",
"Raymond Veldhuis",
"Christoph Brune",
"Nicola Strisciuglio"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Wang_What_do_neural_networks_learn_in_image_classification_A_frequency_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Wang_What_do_neural_networks_learn_in_image_classification_A_frequency_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Wang_What_do_neural_ICCV_2023_supplemental.pdf | 2307.09829 | cvf | @InProceedings{Wang_2023_ICCV,
author = {Wang, Shunxin and Veldhuis, Raymond and Brune, Christoph and Strisciuglio, Nicola},
title = {What do neural networks learn in image classification? A frequency shortcut perspective},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer... | Frequency analysis is useful for understanding the mechanisms of representation learning in neural networks (NNs). Most research in this area focuses on the learning dynamics of NNs for regression tasks, while little for classification. This study empirically investigates the latter and expands the understanding of fre... | [
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72 | Tracking by 3D Model Estimation of Unknown Objects in Videos | [
"Denys Rozumnyi",
"Jiří Matas",
"Marc Pollefeys",
"Vittorio Ferrari",
"Martin R. Oswald"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Rozumnyi_Tracking_by_3D_Model_Estimation_of_Unknown_Objects_in_Videos_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Rozumnyi_Tracking_by_3D_Model_Estimation_of_Unknown_Objects_in_Videos_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Rozumnyi_Tracking_by_3D_ICCV_2023_supplemental.zip | 2304.06419 | cvf | @InProceedings{Rozumnyi_2023_ICCV,
author = {Rozumnyi, Denys and Matas, Ji\v{r}{\'\i} and Pollefeys, Marc and Ferrari, Vittorio and Oswald, Martin R.},
title = {Tracking by 3D Model Estimation of Unknown Objects in Videos},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer... | Most model-free visual object tracking methods formulate the tracking task as object location estimation given by a 2D segmentation or a bounding box in each video frame. We argue that this representation is limited and instead propose to guide and improve 2D tracking with an explicit object representation, namely the ... | [
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73 | ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering | [
"Andrea Ramazzina",
"Mario Bijelic",
"Stefanie Walz",
"Alessandro Sanvito",
"Dominik Scheuble",
"Felix Heide"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Ramazzina_ScatterNeRF_Seeing_Through_Fog_with_Physically-Based_Inverse_Neural_Rendering_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Ramazzina_ScatterNeRF_Seeing_Through_Fog_with_Physically-Based_Inverse_Neural_Rendering_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Ramazzina_ScatterNeRF_Seeing_Through_ICCV_2023_supplemental.pdf | 2305.02103 | cvf | @InProceedings{Ramazzina_2023_ICCV,
author = {Ramazzina, Andrea and Bijelic, Mario and Walz, Stefanie and Sanvito, Alessandro and Scheuble, Dominik and Heide, Felix},
title = {ScatterNeRF: Seeing Through Fog with Physically-Based Inverse Neural Rendering},
booktitle = {Proceedings of the IEEE/CVF Int... | Vision in adverse weather conditions, whether it be snow, rain, or fog is challenging. In these scenarios, scattering and attenuation severly degrades image quality. Handling such inclement weather conditions, however, is essential to operate autonomous vehicles, drones and robotic applications where human performance ... | [
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74 | Sigmoid Loss for Language Image Pre-Training | [
"Xiaohua Zhai",
"Basil Mustafa",
"Alexander Kolesnikov",
"Lucas Beyer"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhai_Sigmoid_Loss_for_Language_Image_Pre-Training_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhai_Sigmoid_Loss_for_Language_Image_Pre-Training_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhai_Sigmoid_Loss_for_ICCV_2023_supplemental.pdf | 2303.15343 | cvf | @InProceedings{Zhai_2023_ICCV,
author = {Zhai, Xiaohua and Mustafa, Basil and Kolesnikov, Alexander and Beyer, Lucas},
title = {Sigmoid Loss for Language Image Pre-Training},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
y... | We propose a simple pairwise sigmoid loss for image-text pre-training. Unlike standard contrastive learning with softmax normalization, the sigmoid loss operates solely on image-text pairs and does not require a global view of the pairwise similarities for normalization. The sigmoid loss simultaneously allows further s... | [
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75 | PromptCap: Prompt-Guided Image Captioning for VQA with GPT-3 | [
"Yushi Hu",
"Hang Hua",
"Zhengyuan Yang",
"Weijia Shi",
"Noah A. Smith",
"Jiebo Luo"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Hu_PromptCap_Prompt-Guided_Image_Captioning_for_VQA_with_GPT-3_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Hu_PromptCap_Prompt-Guided_Image_Captioning_for_VQA_with_GPT-3_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Hu_PromptCap_Prompt-Guided_Image_ICCV_2023_supplemental.pdf | 2211.09699 | title_judge | @InProceedings{Hu_2023_ICCV,
author = {Hu, Yushi and Hua, Hang and Yang, Zhengyuan and Shi, Weijia and Smith, Noah A. and Luo, Jiebo},
title = {PromptCap: Prompt-Guided Image Captioning for VQA with GPT-3},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Knowledge-based visual question answering (VQA) involves questions that require world knowledge beyond the image to yield the correct answer. Large language models (LMs) like GPT-3 are particularly helpful for this task because of their strong knowledge retrieval and reasoning capabilities. To enable LM to understand i... | [
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76 | Neural Video Depth Stabilizer | [
"Yiran Wang",
"Min Shi",
"Jiaqi Li",
"Zihao Huang",
"Zhiguo Cao",
"Jianming Zhang",
"Ke Xian",
"Guosheng Lin"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Wang_Neural_Video_Depth_Stabilizer_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Wang_Neural_Video_Depth_Stabilizer_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Wang_Neural_Video_Depth_ICCV_2023_supplemental.pdf | 2307.08695 | cvf | @InProceedings{Wang_2023_ICCV,
author = {Wang, Yiran and Shi, Min and Li, Jiaqi and Huang, Zihao and Cao, Zhiguo and Zhang, Jianming and Xian, Ke and Lin, Guosheng},
title = {Neural Video Depth Stabilizer},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Video depth estimation aims to infer temporally consistent depth. Some methods achieve temporal consistency by finetuning a single-image depth model during test time using geometry and re-projection constraints, which is inefficient and not robust. An alternative approach is to learn how to enforce temporal consistency... | [
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77 | Learning Symmetry-Aware Geometry Correspondences for 6D Object Pose Estimation | [
"Heng Zhao",
"Shenxing Wei",
"Dahu Shi",
"Wenming Tan",
"Zheyang Li",
"Ye Ren",
"Xing Wei",
"Yi Yang",
"Shiliang Pu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhao_Learning_Symmetry-Aware_Geometry_Correspondences_for_6D_Object_Pose_Estimation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_Learning_Symmetry-Aware_Geometry_Correspondences_for_6D_Object_Pose_Estimation_ICCV_2023_paper.pdf | null | null | null | @InProceedings{Zhao_2023_ICCV,
author = {Zhao, Heng and Wei, Shenxing and Shi, Dahu and Tan, Wenming and Li, Zheyang and Ren, Ye and Wei, Xing and Yang, Yi and Pu, Shiliang},
title = {Learning Symmetry-Aware Geometry Correspondences for 6D Object Pose Estimation},
booktitle = {Proceedings of the IEEE... | Current 6D pose estimation methods focus on handling objects that are previously trained, which limits their applications in real dynamic world. To this end, we propose a geometry correspondence-based framework, termed GCPose, to estimate 6D pose of arbitrary unseen objects without any re-training. Specifically, the pr... | [
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78 | TrackFlow: Multi-Object tracking with Normalizing Flows | [
"Gianluca Mancusi",
"Aniello Panariello",
"Angelo Porrello",
"Matteo Fabbri",
"Simone Calderara",
"Rita Cucchiara"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Mancusi_TrackFlow_Multi-Object_tracking_with_Normalizing_Flows_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Mancusi_TrackFlow_Multi-Object_tracking_with_Normalizing_Flows_ICCV_2023_paper.pdf | null | 2308.11513 | cvf | @InProceedings{Mancusi_2023_ICCV,
author = {Mancusi, Gianluca and Panariello, Aniello and Porrello, Angelo and Fabbri, Matteo and Calderara, Simone and Cucchiara, Rita},
title = {TrackFlow: Multi-Object tracking with Normalizing Flows},
booktitle = {Proceedings of the IEEE/CVF International Conferenc... | The field of multi-object tracking has recently seen a renewed interest in the good old schema of tracking-by-detection, as its simplicity and strong priors spare it from the complex design and painful babysitting of tracking-by-attention approaches. In view of this, we aim at extending tracking-by-detection to multi-m... | [
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79 | Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning | [
"Yuanhao Zhai",
"Tianyu Luan",
"David Doermann",
"Junsong Yuan"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhai_Towards_Generic_Image_Manipulation_Detection_with_Weakly-Supervised_Self-Consistency_Learning_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhai_Towards_Generic_Image_Manipulation_Detection_with_Weakly-Supervised_Self-Consistency_Learning_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhai_Towards_Generic_Image_ICCV_2023_supplemental.pdf | 2309.01246 | cvf | @InProceedings{Zhai_2023_ICCV,
author = {Zhai, Yuanhao and Luan, Tianyu and Doermann, David and Yuan, Junsong},
title = {Towards Generic Image Manipulation Detection with Weakly-Supervised Self-Consistency Learning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision... | As advanced image manipulation techniques emerge, detecting the manipulation becomes increasingly important. Despite the success of recent learning-based approaches for image manipulation detection, they typically require expensive pixel-level annotations to train, while exhibiting degraded performance when testing on ... | [
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80 | PARF: Primitive-Aware Radiance Fusion for Indoor Scene Novel View Synthesis | [
"Haiyang Ying",
"Baowei Jiang",
"Jinzhi Zhang",
"Di Xu",
"Tao Yu",
"Qionghai Dai",
"Lu Fang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Ying_PARF_Primitive-Aware_Radiance_Fusion_for_Indoor_Scene_Novel_View_Synthesis_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Ying_PARF_Primitive-Aware_Radiance_Fusion_for_Indoor_Scene_Novel_View_Synthesis_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Ying_PARF_Primitive-Aware_Radiance_ICCV_2023_supplemental.zip | 2309.17190 | title_snapshot | @InProceedings{Ying_2023_ICCV,
author = {Ying, Haiyang and Jiang, Baowei and Zhang, Jinzhi and Xu, Di and Yu, Tao and Dai, Qionghai and Fang, Lu},
title = {PARF: Primitive-Aware Radiance Fusion for Indoor Scene Novel View Synthesis},
booktitle = {Proceedings of the IEEE/CVF International Conference o... | This paper proposes a method for fast scene radiance field reconstruction with strong novel view synthesis performance and convenient scene editing functionality. The key idea is to fully utilize semantic parsing and primitive extraction for constraining and accelerating the radiance field reconstruction process. To fu... | [
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81 | DeePoint: Visual Pointing Recognition and Direction Estimation | [
"Shu Nakamura",
"Yasutomo Kawanishi",
"Shohei Nobuhara",
"Ko Nishino"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Nakamura_DeePoint_Visual_Pointing_Recognition_and_Direction_Estimation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Nakamura_DeePoint_Visual_Pointing_Recognition_and_Direction_Estimation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Nakamura_DeePoint_Visual_Pointing_ICCV_2023_supplemental.zip | 2304.06977 | cvf | @InProceedings{Nakamura_2023_ICCV,
author = {Nakamura, Shu and Kawanishi, Yasutomo and Nobuhara, Shohei and Nishino, Ko},
title = {DeePoint: Visual Pointing Recognition and Direction Estimation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | In this paper, we realize automatic visual recognition and direction estimation of pointing. We introduce the first neural pointing understanding method based on two key contributions. The first is the introduction of a first-of-its-kind large-scale dataset for pointing recognition and direction estimation, which we re... | [
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82 | Periodically Exchange Teacher-Student for Source-Free Object Detection | [
"Qipeng Liu",
"Luojun Lin",
"Zhifeng Shen",
"Zhifeng Yang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Liu_Periodically_Exchange_Teacher-Student_for_Source-Free_Object_Detection_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_Periodically_Exchange_Teacher-Student_for_Source-Free_Object_Detection_ICCV_2023_paper.pdf | null | 2311.13930 | title_snapshot | @InProceedings{Liu_2023_ICCV,
author = {Liu, Qipeng and Lin, Luojun and Shen, Zhifeng and Yang, Zhifeng},
title = {Periodically Exchange Teacher-Student for Source-Free Object Detection},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {Oc... | Source-free object detection (SFOD) aims to adapt the source detector to unlabeled target domain data in the absence of source domain data. Most SFOD methods follow the same self-training paradigm using mean-teacher (MT) framework where the student model is guided by only one single teacher model. However, such paradig... | [
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83 | Generating Instance-level Prompts for Rehearsal-free Continual Learning | [
"Dahuin Jung",
"Dongyoon Han",
"Jihwan Bang",
"Hwanjun Song"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Jung_Generating_Instance-level_Prompts_for_Rehearsal-free_Continual_Learning_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Jung_Generating_Instance-level_Prompts_for_Rehearsal-free_Continual_Learning_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Jung_Generating_Instance-level_Prompts_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Jung_2023_ICCV,
author = {Jung, Dahuin and Han, Dongyoon and Bang, Jihwan and Song, Hwanjun},
title = {Generating Instance-level Prompts for Rehearsal-free Continual Learning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month =... | We introduce Domain-Adaptive Prompt (DAP), a novel method for continual learning using Vision Transformers (ViT). Prompt-based continual learning has recently gained attention due to its rehearsal-free nature. Currently, the prompt pool, which is suggested by prompt-based continual learning, is key to effectively explo... | [
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84 | Deformer: Dynamic Fusion Transformer for Robust Hand Pose Estimation | [
"Qichen Fu",
"Xingyu Liu",
"Ran Xu",
"Juan Carlos Niebles",
"Kris M. Kitani"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Fu_Deformer_Dynamic_Fusion_Transformer_for_Robust_Hand_Pose_Estimation_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Fu_Deformer_Dynamic_Fusion_Transformer_for_Robust_Hand_Pose_Estimation_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Fu_Deformer_Dynamic_Fusion_ICCV_2023_supplemental.pdf | 2303.04991 | cvf | @InProceedings{Fu_2023_ICCV,
author = {Fu, Qichen and Liu, Xingyu and Xu, Ran and Niebles, Juan Carlos and Kitani, Kris M.},
title = {Deformer: Dynamic Fusion Transformer for Robust Hand Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Accurately estimating 3D hand pose is crucial for understanding how humans interact with the world. Despite remarkable progress, existing methods often struggle to generate plausible hand poses when the hand is heavily occluded or blurred. In videos, the movements of the hand allow us to observe various parts of the ha... | [
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85 | HSE: Hybrid Species Embedding for Deep Metric Learning | [
"Bailin Yang",
"Haoqiang Sun",
"Frederick W. B. Li",
"Zheng Chen",
"Jianlu Cai",
"Chao Song"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Yang_HSE_Hybrid_Species_Embedding_for_Deep_Metric_Learning_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Yang_HSE_Hybrid_Species_Embedding_for_Deep_Metric_Learning_ICCV_2023_paper.pdf | null | null | null | @InProceedings{Yang_2023_ICCV,
author = {Yang, Bailin and Sun, Haoqiang and Li, Frederick W. B. and Chen, Zheng and Cai, Jianlu and Song, Chao},
title = {HSE: Hybrid Species Embedding for Deep Metric Learning},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV... | Deep metric learning is crucial for finding an embedding function that can generalize to training and testing data, including unknown test classes. However, limited training samples restrict the model's generalization to downstream tasks. While adding new training samples is a promising solution, determining their labe... | [
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86 | Online Continual Learning on Hierarchical Label Expansion | [
"Byung Hyun Lee",
"Okchul Jung",
"Jonghyun Choi",
"Se Young Chun"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Lee_Online_Continual_Learning_on_Hierarchical_Label_Expansion_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Lee_Online_Continual_Learning_on_Hierarchical_Label_Expansion_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Lee_Online_Continual_Learning_ICCV_2023_supplemental.pdf | 2308.14374 | cvf | @InProceedings{Lee_2023_ICCV,
author = {Lee, Byung Hyun and Jung, Okchul and Choi, Jonghyun and Chun, Se Young},
title = {Online Continual Learning on Hierarchical Label Expansion},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October}... | Continual learning (CL) enables models to adapt to new tasks and environments without forgetting previously learned knowledge. While current CL setups have ignored the relationship between labels in the past task and the new task with or without small task overlaps, real-world scenarios often involve hierarchical relat... | [
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87 | iDAG: Invariant DAG Searching for Domain Generalization | [
"Zenan Huang",
"Haobo Wang",
"Junbo Zhao",
"Nenggan Zheng"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Huang_iDAG_Invariant_DAG_Searching_for_Domain_Generalization_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Huang_iDAG_Invariant_DAG_Searching_for_Domain_Generalization_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Huang_iDAG_Invariant_DAG_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Huang_2023_ICCV,
author = {Huang, Zenan and Wang, Haobo and Zhao, Junbo and Zheng, Nenggan},
title = {iDAG: Invariant DAG Searching for Domain Generalization},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
y... | Existing machine learning (ML) models are often fragile in open environments because the data distribution frequently shifts. To address this problem, domain generalization (DG) aims to explore underlying invariant patterns for stable prediction across domains. In this work, we first characterize that this failure of c... | [
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88 | Spacetime Surface Regularization for Neural Dynamic Scene Reconstruction | [
"Jaesung Choe",
"Christopher Choy",
"Jaesik Park",
"In So Kweon",
"Anima Anandkumar"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Choe_Spacetime_Surface_Regularization_for_Neural_Dynamic_Scene_Reconstruction_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Choe_Spacetime_Surface_Regularization_for_Neural_Dynamic_Scene_Reconstruction_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Choe_Spacetime_Surface_Regularization_ICCV_2023_supplemental.zip | null | null | @InProceedings{Choe_2023_ICCV,
author = {Choe, Jaesung and Choy, Christopher and Park, Jaesik and Kweon, In So and Anandkumar, Anima},
title = {Spacetime Surface Regularization for Neural Dynamic Scene Reconstruction},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Visi... | We propose an algorithm, 4DRegSDF, for the spacetime surface regularization to improve the fidelity of neural rendering and reconstruction in dynamic scenes. The key idea is to impose local rigidity on the deformable Signed Distance Function (SDF) for temporal coherency. Our approach works by (1) sampling points on the... | [
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89 | GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes | [
"Chaoqiang Zhao",
"Matteo Poggi",
"Fabio Tosi",
"Lei Zhou",
"Qiyu Sun",
"Yang Tang",
"Stefano Mattoccia"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhao_GasMono_Geometry-Aided_Self-Supervised_Monocular_Depth_Estimation_for_Indoor_Scenes_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_GasMono_Geometry-Aided_Self-Supervised_Monocular_Depth_Estimation_for_Indoor_Scenes_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhao_GasMono_Geometry-Aided_Self-Supervised_ICCV_2023_supplemental.pdf | 2309.16019 | title_snapshot | @InProceedings{Zhao_2023_ICCV,
author = {Zhao, Chaoqiang and Poggi, Matteo and Tosi, Fabio and Zhou, Lei and Sun, Qiyu and Tang, Yang and Mattoccia, Stefano},
title = {GasMono: Geometry-Aided Self-Supervised Monocular Depth Estimation for Indoor Scenes},
booktitle = {Proceedings of the IEEE/CVF Inter... | This paper tackles the challenges of self-supervised monocular depth estimation in indoor scenes caused by large rotation between frames and low texture. We ease the learning process by obtaining coarse camera poses from monocular sequences through multi-view geometry to deal with the former. However, we found that lim... | [
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90 | 3D Motion Magnification: Visualizing Subtle Motions from Time-Varying Radiance Fields | [
"Brandon Y. Feng",
"Hadi Alzayer",
"Michael Rubinstein",
"William T. Freeman",
"Jia-bin Huang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Feng_3D_Motion_Magnification_Visualizing_Subtle_Motions_from_Time-Varying_Radiance_Fields_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Feng_3D_Motion_Magnification_Visualizing_Subtle_Motions_from_Time-Varying_Radiance_Fields_ICCV_2023_paper.pdf | null | 2308.03757 | title_judge | @InProceedings{Feng_2023_ICCV,
author = {Feng, Brandon Y. and Alzayer, Hadi and Rubinstein, Michael and Freeman, William T. and Huang, Jia-bin},
title = {3D Motion Magnification: Visualizing Subtle Motions from Time-Varying Radiance Fields},
booktitle = {Proceedings of the IEEE/CVF International Conf... | Motion magnification helps us visualize subtle, imperceptible motion. However, prior methods only work for 2D videos captured with a fixed camera. We present a 3D motion magnification method that can magnify subtle motions from scenes captured by a moving camera, while supporting novel view rendering. We represent the ... | [
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91 | Learning to Transform for Generalizable Instance-wise Invariance | [
"Utkarsh Singhal",
"Carlos Esteves",
"Ameesh Makadia",
"Stella X. Yu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Singhal_Learning_to_Transform_for_Generalizable_Instance-wise_Invariance_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Singhal_Learning_to_Transform_for_Generalizable_Instance-wise_Invariance_ICCV_2023_paper.pdf | null | 2309.16672 | title_snapshot | @InProceedings{Singhal_2023_ICCV,
author = {Singhal, Utkarsh and Esteves, Carlos and Makadia, Ameesh and Yu, Stella X.},
title = {Learning to Transform for Generalizable Instance-wise Invariance},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month ... | Computer vision research has long aimed to build systems that are robust to transformations found in natural data. Traditionally, this is done using data augmentation or hard-coding invariances into the architecture.
However, too much or too little invariance can hurt, and the correct amount is unknown a priori and d... | [
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92 | Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning | [
"Xiaobao Guo",
"Nithish Muthuchamy Selvaraj",
"Zitong Yu",
"Adams Wai-Kin Kong",
"Bingquan Shen",
"Alex Kot"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Guo_Audio-Visual_Deception_Detection_DOLOS_Dataset_and_Parameter-Efficient_Crossmodal_Learning_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Guo_Audio-Visual_Deception_Detection_DOLOS_Dataset_and_Parameter-Efficient_Crossmodal_Learning_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Guo_Audio-Visual_Deception_Detection_ICCV_2023_supplemental.pdf | 2303.12745 | cvf | @InProceedings{Guo_2023_ICCV,
author = {Guo, Xiaobao and Selvaraj, Nithish Muthuchamy and Yu, Zitong and Kong, Adams Wai-Kin and Shen, Bingquan and Kot, Alex},
title = {Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning},
booktitle = {Proceedings of the IEEE/C... | Deception detection in conversations is a challenging yet important task, having pivotal applications in many fields such as credibility assessment in business, multimedia anti-frauds, and custom security. Despite this, deception detection research is hindered by the lack of high-quality deception datasets, as well as ... | [
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93 | Multiple Instance Learning Framework with Masked Hard Instance Mining for Whole Slide Image Classification | [
"Wenhao Tang",
"Sheng Huang",
"Xiaoxian Zhang",
"Fengtao Zhou",
"Yi Zhang",
"Bo Liu"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Tang_Multiple_Instance_Learning_Framework_with_Masked_Hard_Instance_Mining_for_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Tang_Multiple_Instance_Learning_Framework_with_Masked_Hard_Instance_Mining_for_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Tang_Multiple_Instance_Learning_ICCV_2023_supplemental.pdf | 2307.15254 | cvf | @InProceedings{Tang_2023_ICCV,
author = {Tang, Wenhao and Huang, Sheng and Zhang, Xiaoxian and Zhou, Fengtao and Zhang, Yi and Liu, Bo},
title = {Multiple Instance Learning Framework with Masked Hard Instance Mining for Whole Slide Image Classification},
booktitle = {Proceedings of the IEEE/CVF Inter... | The whole slide image (WSI) classification is often formulated as a multiple instance learning (MIL) problem. Since the positive tissue is only a small fraction of the gigapixel WSI, existing MIL methods intuitively focus on identifying salient instances via attention mechanisms. However, this leads to a bias towards e... | [
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94 | Unsupervised Compositional Concepts Discovery with Text-to-Image Generative Models | [
"Nan Liu",
"Yilun Du",
"Shuang Li",
"Joshua B. Tenenbaum",
"Antonio Torralba"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Liu_Unsupervised_Compositional_Concepts_Discovery_with_Text-to-Image_Generative_Models_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Liu_Unsupervised_Compositional_Concepts_Discovery_with_Text-to-Image_Generative_Models_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Liu_Unsupervised_Compositional_Concepts_ICCV_2023_supplemental.pdf | 2306.05357 | cvf | @InProceedings{Liu_2023_ICCV,
author = {Liu, Nan and Du, Yilun and Li, Shuang and Tenenbaum, Joshua B. and Torralba, Antonio},
title = {Unsupervised Compositional Concepts Discovery with Text-to-Image Generative Models},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vi... | Text-to-image generative models have enabled high-resolution image synthesis across different domains, but require users to specify the content they wish to generate. In this paper, we consider the inverse problem - given a collection of different images, can we discover the generative concepts that represent each imag... | [
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95 | Partition-And-Debias: Agnostic Biases Mitigation via a Mixture of Biases-Specific Experts | [
"Jiaxuan Li",
"Duc Minh Vo",
"Hideki Nakayama"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Li_Partition-And-Debias_Agnostic_Biases_Mitigation_via_a_Mixture_of_Biases-Specific_Experts_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Li_Partition-And-Debias_Agnostic_Biases_Mitigation_via_a_Mixture_of_Biases-Specific_Experts_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Li_Partition-And-Debias_Agnostic_Biases_ICCV_2023_supplemental.pdf | 2308.10005 | title_snapshot | @InProceedings{Li_2023_ICCV,
author = {Li, Jiaxuan and Vo, Duc Minh and Nakayama, Hideki},
title = {Partition-And-Debias: Agnostic Biases Mitigation via a Mixture of Biases-Specific Experts},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month =... | Bias mitigation in image classification has been widely researched, and existing methods have yielded notable results. However, most of these methods implicitly assume that a given image contains only one type of known or unknown bias, failing to consider the complexities of real-world biases. We introduce a more chall... | [
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96 | Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes | [
"Di Wu",
"Pengfei Chen",
"Xuehui Yu",
"Guorong Li",
"Zhenjun Han",
"Jianbin Jiao"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Wu_Spatial_Self-Distillation_for_Object_Detection_with_Inaccurate_Bounding_Boxes_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Wu_Spatial_Self-Distillation_for_Object_Detection_with_Inaccurate_Bounding_Boxes_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Wu_Spatial_Self-Distillation_for_ICCV_2023_supplemental.pdf | 2307.12101 | cvf | @InProceedings{Wu_2023_ICCV,
author = {Wu, Di and Chen, Pengfei and Yu, Xuehui and Li, Guorong and Han, Zhenjun and Jiao, Jianbin},
title = {Spatial Self-Distillation for Object Detection with Inaccurate Bounding Boxes},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vi... | Object detection via inaccurate bounding box supervision has boosted a broad interest due to the expensive high-quality annotation data or the occasional inevitability of low annotation quality (e.g. tiny objects). The previous works usually utilize multiple instance learning (MIL), which highly depends on category inf... | [
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97 | CC3D: Layout-Conditioned Generation of Compositional 3D Scenes | [
"Sherwin Bahmani",
"Jeong Joon Park",
"Despoina Paschalidou",
"Xingguang Yan",
"Gordon Wetzstein",
"Leonidas Guibas",
"Andrea Tagliasacchi"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Bahmani_CC3D_Layout-Conditioned_Generation_of_Compositional_3D_Scenes_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Bahmani_CC3D_Layout-Conditioned_Generation_of_Compositional_3D_Scenes_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Bahmani_CC3D_Layout-Conditioned_Generation_ICCV_2023_supplemental.pdf | 2303.12074 | cvf | @InProceedings{Bahmani_2023_ICCV,
author = {Bahmani, Sherwin and Park, Jeong Joon and Paschalidou, Despoina and Yan, Xingguang and Wetzstein, Gordon and Guibas, Leonidas and Tagliasacchi, Andrea},
title = {CC3D: Layout-Conditioned Generation of Compositional 3D Scenes},
booktitle = {Proceedings of th... | In this work, we introduce CC3D, a conditional generative model that synthesizes complex 3D scenes conditioned on 2D semantic scene layouts, trained using single-view images. Different from most existing 3D GANs that limit their applicability to aligned single objects, we focus on generating complex scenes with multipl... | [
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98 | Alleviating Catastrophic Forgetting of Incremental Object Detection via Within-Class and Between-Class Knowledge Distillation | [
"Mengxue Kang",
"Jinpeng Zhang",
"Jinming Zhang",
"Xiashuang Wang",
"Yang Chen",
"Zhe Ma",
"Xuhui Huang"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Kang_Alleviating_Catastrophic_Forgetting_of_Incremental_Object_Detection_via_Within-Class_and_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Kang_Alleviating_Catastrophic_Forgetting_of_Incremental_Object_Detection_via_Within-Class_and_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Kang_Alleviating_Catastrophic_Forgetting_ICCV_2023_supplemental.pdf | null | null | @InProceedings{Kang_2023_ICCV,
author = {Kang, Mengxue and Zhang, Jinpeng and Zhang, Jinming and Wang, Xiashuang and Chen, Yang and Ma, Zhe and Huang, Xuhui},
title = {Alleviating Catastrophic Forgetting of Incremental Object Detection via Within-Class and Between-Class Knowledge Distillation},
bookt... | Incremental object detection (IOD) task requires a model to learn continually from newly added data. However, directly fine-tuning a well-trained detection model on a new task will sharply decrease the performance on old tasks, which is known as catastrophic forgetting. Knowledge distillation, including feature distill... | [
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99 | TextPSG: Panoptic Scene Graph Generation from Textual Descriptions | [
"Chengyang Zhao",
"Yikang Shen",
"Zhenfang Chen",
"Mingyu Ding",
"Chuang Gan"
] | https://openaccess.thecvf.com/content/ICCV2023/html/Zhao_TextPSG_Panoptic_Scene_Graph_Generation_from_Textual_Descriptions_ICCV_2023_paper.html | https://openaccess.thecvf.com/content/ICCV2023/papers/Zhao_TextPSG_Panoptic_Scene_Graph_Generation_from_Textual_Descriptions_ICCV_2023_paper.pdf | https://openaccess.thecvf.com/content/ICCV2023/supplemental/Zhao_TextPSG_Panoptic_Scene_Graph_Generation_from_Textual_Descriptions_ICCV_2023_supplemental.pdf | 2310.07056 | title_snapshot | @InProceedings{Zhao_2023_ICCV,
author = {Zhao, Chengyang and Shen, Yikang and Chen, Zhenfang and Ding, Mingyu and Gan, Chuang},
title = {TextPSG: Panoptic Scene Graph Generation from Textual Descriptions},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
... | Panoptic Scene Graph has recently been proposed for comprehensive scene understanding. However, previous works adopt a fully-supervised learning manner, requiring large amounts of pixel-wise densely-annotated data, which is always tedious and expensive to obtain. To address this limitation, we study a new problem of Pa... | [
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