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0 | GFPose: Learning 3D Human Pose Prior With Gradient Fields | [
"Hai Ci",
"Mingdong Wu",
"Wentao Zhu",
"Xiaoxuan Ma",
"Hao Dong",
"Fangwei Zhong",
"Yizhou Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ci_GFPose_Learning_3D_Human_Pose_Prior_With_Gradient_Fields_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ci_GFPose_Learning_3D_Human_Pose_Prior_With_Gradient_Fields_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Ci_GFPose_Learning_3D_CVPR_2023_supplemental.pdf | 2212.08641 | cvf | @InProceedings{Ci_2023_CVPR,
author = {Ci, Hai and Wu, Mingdong and Zhu, Wentao and Ma, Xiaoxuan and Dong, Hao and Zhong, Fangwei and Wang, Yizhou},
title = {GFPose: Learning 3D Human Pose Prior With Gradient Fields},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern ... | Learning 3D human pose prior is essential to human-centered AI. Here, we present GFPose, a versatile framework to model plausible 3D human poses for various applications. At the core of GFPose is a time-dependent score network, which estimates the gradient on each body joint and progressively denoises the perturbed 3D ... | [
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1 | CXTrack: Improving 3D Point Cloud Tracking With Contextual Information | [
"Tian-Xing Xu",
"Yuan-Chen Guo",
"Yu-Kun Lai",
"Song-Hai Zhang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Xu_CXTrack_Improving_3D_Point_Cloud_Tracking_With_Contextual_Information_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Xu_CXTrack_Improving_3D_Point_Cloud_Tracking_With_Contextual_Information_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Xu_CXTrack_Improving_3D_CVPR_2023_supplemental.pdf | 2211.08542 | cvf | @InProceedings{Xu_2023_CVPR,
author = {Xu, Tian-Xing and Guo, Yuan-Chen and Lai, Yu-Kun and Zhang, Song-Hai},
title = {CXTrack: Improving 3D Point Cloud Tracking With Contextual Information},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
m... | 3D single object tracking plays an essential role in many applications, such as autonomous driving. It remains a challenging problem due to the large appearance variation and the sparsity of points caused by occlusion and limited sensor capabilities. Therefore, contextual information across two consecutive frames is cr... | [
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2 | Deep Frequency Filtering for Domain Generalization | [
"Shiqi Lin",
"Zhizheng Zhang",
"Zhipeng Huang",
"Yan Lu",
"Cuiling Lan",
"Peng Chu",
"Quanzeng You",
"Jiang Wang",
"Zicheng Liu",
"Amey Parulkar",
"Viraj Navkal",
"Zhibo Chen"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Lin_Deep_Frequency_Filtering_for_Domain_Generalization_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Lin_Deep_Frequency_Filtering_for_Domain_Generalization_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Lin_Deep_Frequency_Filtering_CVPR_2023_supplemental.pdf | 2203.12198 | cvf | @InProceedings{Lin_2023_CVPR,
author = {Lin, Shiqi and Zhang, Zhizheng and Huang, Zhipeng and Lu, Yan and Lan, Cuiling and Chu, Peng and You, Quanzeng and Wang, Jiang and Liu, Zicheng and Parulkar, Amey and Navkal, Viraj and Chen, Zhibo},
title = {Deep Frequency Filtering for Domain Generalization},
... | Improving the generalization ability of Deep Neural Networks (DNNs) is critical for their practical uses, which has been a longstanding challenge. Some theoretical studies have uncovered that DNNs have preferences for some frequency components in the learning process and indicated that this may affect the robustness of... | [
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3 | Frame Flexible Network | [
"Yitian Zhang",
"Yue Bai",
"Chang Liu",
"Huan Wang",
"Sheng Li",
"Yun Fu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_Frame_Flexible_Network_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Frame_Flexible_Network_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhang_Frame_Flexible_Network_CVPR_2023_supplemental.pdf | 2303.14817 | cvf | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Yitian and Bai, Yue and Liu, Chang and Wang, Huan and Li, Sheng and Fu, Yun},
title = {Frame Flexible Network},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | Existing video recognition algorithms always conduct different training pipelines for inputs with different frame numbers, which requires repetitive training operations and multiplying storage costs. If we evaluate the model using other frames which are not used in training, we observe the performance will drop signifi... | [
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4 | Unsupervised Cumulative Domain Adaptation for Foggy Scene Optical Flow | [
"Hanyu Zhou",
"Yi Chang",
"Wending Yan",
"Luxin Yan"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhou_Unsupervised_Cumulative_Domain_Adaptation_for_Foggy_Scene_Optical_Flow_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhou_Unsupervised_Cumulative_Domain_Adaptation_for_Foggy_Scene_Optical_Flow_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhou_Unsupervised_Cumulative_Domain_CVPR_2023_supplemental.zip | 2303.07564 | cvf | @InProceedings{Zhou_2023_CVPR,
author = {Zhou, Hanyu and Chang, Yi and Yan, Wending and Yan, Luxin},
title = {Unsupervised Cumulative Domain Adaptation for Foggy Scene Optical Flow},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | Optical flow has achieved great success under clean scenes, but suffers from restricted performance under foggy scenes. To bridge the clean-to-foggy domain gap, the existing methods typically adopt the domain adaptation to transfer the motion knowledge from clean to synthetic foggy domain. However, these methods unexpe... | [
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5 | NoisyTwins: Class-Consistent and Diverse Image Generation Through StyleGANs | [
"Harsh Rangwani",
"Lavish Bansal",
"Kartik Sharma",
"Tejan Karmali",
"Varun Jampani",
"R. Venkatesh Babu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Rangwani_NoisyTwins_Class-Consistent_and_Diverse_Image_Generation_Through_StyleGANs_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Rangwani_NoisyTwins_Class-Consistent_and_Diverse_Image_Generation_Through_StyleGANs_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Rangwani_NoisyTwins_Class-Consistent_and_CVPR_2023_supplemental.pdf | 2304.05866 | cvf | @InProceedings{Rangwani_2023_CVPR,
author = {Rangwani, Harsh and Bansal, Lavish and Sharma, Kartik and Karmali, Tejan and Jampani, Varun and Babu, R. Venkatesh},
title = {NoisyTwins: Class-Consistent and Diverse Image Generation Through StyleGANs},
booktitle = {Proceedings of the IEEE/CVF Conference ... | StyleGANs are at the forefront of controllable image generation as they produce a latent space that is semantically disentangled, making it suitable for image editing and manipulation. However, the performance of StyleGANs severely degrades when trained via class-conditioning on large-scale long-tailed datasets. We fin... | [
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6 | DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-Aware Scene Synthesis | [
"Yinghao Xu",
"Menglei Chai",
"Zifan Shi",
"Sida Peng",
"Ivan Skorokhodov",
"Aliaksandr Siarohin",
"Ceyuan Yang",
"Yujun Shen",
"Hsin-Ying Lee",
"Bolei Zhou",
"Sergey Tulyakov"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Xu_DisCoScene_Spatially_Disentangled_Generative_Radiance_Fields_for_Controllable_3D-Aware_Scene_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Xu_DisCoScene_Spatially_Disentangled_Generative_Radiance_Fields_for_Controllable_3D-Aware_Scene_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Xu_DisCoScene_Spatially_Disentangled_CVPR_2023_supplemental.pdf | 2212.11984 | cvf | @InProceedings{Xu_2023_CVPR,
author = {Xu, Yinghao and Chai, Menglei and Shi, Zifan and Peng, Sida and Skorokhodov, Ivan and Siarohin, Aliaksandr and Yang, Ceyuan and Shen, Yujun and Lee, Hsin-Ying and Zhou, Bolei and Tulyakov, Sergey},
title = {DisCoScene: Spatially Disentangled Generative Radiance Fiel... | Existing 3D-aware image synthesis approaches mainly focus on generating a single canonical object and show limited capacity in composing a complex scene containing a variety of objects. This work presents DisCoScene: a 3D-aware generative model for high-quality and controllable scene synthesis. The key ingredient of ou... | [
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7 | Revisiting Self-Similarity: Structural Embedding for Image Retrieval | [
"Seongwon Lee",
"Suhyeon Lee",
"Hongje Seong",
"Euntai Kim"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Lee_Revisiting_Self-Similarity_Structural_Embedding_for_Image_Retrieval_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Lee_Revisiting_Self-Similarity_Structural_Embedding_for_Image_Retrieval_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Lee_Revisiting_Self-Similarity_Structural_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Lee_2023_CVPR,
author = {Lee, Seongwon and Lee, Suhyeon and Seong, Hongje and Kim, Euntai},
title = {Revisiting Self-Similarity: Structural Embedding for Image Retrieval},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | Despite advances in global image representation, existing image retrieval approaches rarely consider geometric structure during the global retrieval stage. In this work, we revisit the conventional self-similarity descriptor from a convolutional perspective, to encode both the visual and structural cues of the image to... | [
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8 | Minimizing the Accumulated Trajectory Error To Improve Dataset Distillation | [
"Jiawei Du",
"Yidi Jiang",
"Vincent Y. F. Tan",
"Joey Tianyi Zhou",
"Haizhou Li"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Du_Minimizing_the_Accumulated_Trajectory_Error_To_Improve_Dataset_Distillation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Du_Minimizing_the_Accumulated_Trajectory_Error_To_Improve_Dataset_Distillation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Du_Minimizing_the_Accumulated_CVPR_2023_supplemental.pdf | 2211.11004 | cvf | @InProceedings{Du_2023_CVPR,
author = {Du, Jiawei and Jiang, Yidi and Tan, Vincent Y. F. and Zhou, Joey Tianyi and Li, Haizhou},
title = {Minimizing the Accumulated Trajectory Error To Improve Dataset Distillation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Re... | Model-based deep learning has achieved astounding successes due in part to the availability of large-scale real-world data. However, processing such massive amounts of data comes at a considerable cost in terms of computations, storage, training and the search for good neural architectures. Dataset distillation has thu... | [
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9 | Decoupling-and-Aggregating for Image Exposure Correction | [
"Yang Wang",
"Long Peng",
"Liang Li",
"Yang Cao",
"Zheng-Jun Zha"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wang_Decoupling-and-Aggregating_for_Image_Exposure_Correction_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wang_Decoupling-and-Aggregating_for_Image_Exposure_Correction_CVPR_2023_paper.pdf | null | null | null | @InProceedings{Wang_2023_CVPR,
author = {Wang, Yang and Peng, Long and Li, Liang and Cao, Yang and Zha, Zheng-Jun},
title = {Decoupling-and-Aggregating for Image Exposure Correction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | The images captured under improper exposure conditions often suffer from contrast degradation and detail distortion. Contrast degradation will destroy the statistical properties of low-frequency components, while detail distortion will disturb the structural properties of high-frequency components, leading to the low-f... | [
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10 | Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving | [
"Ben Agro",
"Quinlan Sykora",
"Sergio Casas",
"Raquel Urtasun"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Agro_Implicit_Occupancy_Flow_Fields_for_Perception_and_Prediction_in_Self-Driving_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Agro_Implicit_Occupancy_Flow_Fields_for_Perception_and_Prediction_in_Self-Driving_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Agro_Implicit_Occupancy_Flow_CVPR_2023_supplemental.zip | 2308.01471 | title_snapshot | @InProceedings{Agro_2023_CVPR,
author = {Agro, Ben and Sykora, Quinlan and Casas, Sergio and Urtasun, Raquel},
title = {Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}... | A self-driving vehicle (SDV) must be able to perceive its surroundings and predict the future behavior of other traffic participants. Existing works either perform object detection followed by trajectory forecasting of the detected objects, or predict dense occupancy and flow grids for the whole scene. The former poses... | [
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11 | CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes | [
"Harshil Bhatia",
"Edith Tretschk",
"Zorah Lähner",
"Marcel Seelbach Benkner",
"Michael Moeller",
"Christian Theobalt",
"Vladislav Golyanik"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Bhatia_CCuantuMM_Cycle-Consistent_Quantum-Hybrid_Matching_of_Multiple_Shapes_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Bhatia_CCuantuMM_Cycle-Consistent_Quantum-Hybrid_Matching_of_Multiple_Shapes_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Bhatia_CCuantuMM_Cycle-Consistent_Quantum-Hybrid_CVPR_2023_supplemental.zip | 2303.16202 | title_snapshot | @InProceedings{Bhatia_2023_CVPR,
author = {Bhatia, Harshil and Tretschk, Edith and L\"ahner, Zorah and Benkner, Marcel Seelbach and Moeller, Michael and Theobalt, Christian and Golyanik, Vladislav},
title = {CCuantuMM: Cycle-Consistent Quantum-Hybrid Matching of Multiple Shapes},
booktitle = {Proceed... | Jointly matching multiple, non-rigidly deformed 3D shapes is a challenging, NP-hard problem. A perfect matching is necessarily cycle-consistent: Following the pairwise point correspondences along several shapes must end up at the starting vertex of the original shape. Unfortunately, existing quantum shape-matching meth... | [
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12 | TrojViT: Trojan Insertion in Vision Transformers | [
"Mengxin Zheng",
"Qian Lou",
"Lei Jiang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zheng_TrojViT_Trojan_Insertion_in_Vision_Transformers_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zheng_TrojViT_Trojan_Insertion_in_Vision_Transformers_CVPR_2023_paper.pdf | null | 2208.13049 | cvf | @InProceedings{Zheng_2023_CVPR,
author = {Zheng, Mengxin and Lou, Qian and Jiang, Lei},
title = {TrojViT: Trojan Insertion in Vision Transformers},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
... | Vision Transformers (ViTs) have demonstrated the state-of-the-art performance in various vision-related tasks. The success of ViTs motivates adversaries to perform backdoor attacks on ViTs. Although the vulnerability of traditional CNNs to backdoor attacks is well-known, backdoor attacks on ViTs are seldom-studied. Com... | [
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13 | MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds | [
"Jiahui Liu",
"Chirui Chang",
"Jianhui Liu",
"Xiaoyang Wu",
"Lan Ma",
"Xiaojuan Qi"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Liu_MarS3D_A_Plug-and-Play_Motion-Aware_Model_for_Semantic_Segmentation_on_Multi-Scan_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Liu_MarS3D_A_Plug-and-Play_Motion-Aware_Model_for_Semantic_Segmentation_on_Multi-Scan_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Liu_MarS3D_A_Plug-and-Play_CVPR_2023_supplemental.pdf | 2307.09316 | title_snapshot | @InProceedings{Liu_2023_CVPR,
author = {Liu, Jiahui and Chang, Chirui and Liu, Jianhui and Wu, Xiaoyang and Ma, Lan and Qi, Xiaojuan},
title = {MarS3D: A Plug-and-Play Motion-Aware Model for Semantic Segmentation on Multi-Scan 3D Point Clouds},
booktitle = {Proceedings of the IEEE/CVF Conference on C... | 3D semantic segmentation on multi-scan large-scale point clouds plays an important role in autonomous systems. Unlike the single-scan-based semantic segmentation task, this task requires distinguishing the motion states of points in addition to their semantic categories. However, methods designed for single-scan-based ... | [
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14 | An Image Quality Assessment Dataset for Portraits | [
"Nicolas Chahine",
"Stefania Calarasanu",
"Davide Garcia-Civiero",
"Théo Cayla",
"Sira Ferradans",
"Jean Ponce"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Chahine_An_Image_Quality_Assessment_Dataset_for_Portraits_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Chahine_An_Image_Quality_Assessment_Dataset_for_Portraits_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Chahine_An_Image_Quality_CVPR_2023_supplemental.pdf | 2304.05772 | cvf | @InProceedings{Chahine_2023_CVPR,
author = {Chahine, Nicolas and Calarasanu, Stefania and Garcia-Civiero, Davide and Cayla, Th\'eo and Ferradans, Sira and Ponce, Jean},
title = {An Image Quality Assessment Dataset for Portraits},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision ... | Year after year, the demand for ever-better smartphone photos continues to grow, in particular in the domain of portrait photography. Manufacturers thus use perceptual quality criteria throughout the development of smartphone cameras. This costly procedure can be partially replaced by automated learning-based methods f... | [
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15 | MSeg3D: Multi-Modal 3D Semantic Segmentation for Autonomous Driving | [
"Jiale Li",
"Hang Dai",
"Hao Han",
"Yong Ding"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_MSeg3D_Multi-Modal_3D_Semantic_Segmentation_for_Autonomous_Driving_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_MSeg3D_Multi-Modal_3D_Semantic_Segmentation_for_Autonomous_Driving_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_MSeg3D_Multi-Modal_3D_CVPR_2023_supplemental.pdf | 2303.08600 | cvf | @InProceedings{Li_2023_CVPR,
author = {Li, Jiale and Dai, Hang and Han, Hao and Ding, Yong},
title = {MSeg3D: Multi-Modal 3D Semantic Segmentation for Autonomous Driving},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
... | LiDAR and camera are two modalities available for 3D semantic segmentation in autonomous driving. The popular LiDAR-only methods severely suffer from inferior segmentation on small and distant objects due to insufficient laser points, while the robust multi-modal solution is under-explored, where we investigate three c... | [
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16 | Robust Outlier Rejection for 3D Registration With Variational Bayes | [
"Haobo Jiang",
"Zheng Dang",
"Zhen Wei",
"Jin Xie",
"Jian Yang",
"Mathieu Salzmann"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Jiang_Robust_Outlier_Rejection_for_3D_Registration_With_Variational_Bayes_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Jiang_Robust_Outlier_Rejection_for_3D_Registration_With_Variational_Bayes_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Jiang_Robust_Outlier_Rejection_CVPR_2023_supplemental.pdf | 2304.01514 | cvf | @InProceedings{Jiang_2023_CVPR,
author = {Jiang, Haobo and Dang, Zheng and Wei, Zhen and Xie, Jin and Yang, Jian and Salzmann, Mathieu},
title = {Robust Outlier Rejection for 3D Registration With Variational Bayes},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Re... | Learning-based outlier (mismatched correspondence) rejection for robust 3D registration generally formulates the outlier removal as an inlier/outlier classification problem. The core for this to be successful is to learn the discriminative inlier/outlier feature representations. In this paper, we develop a novel variat... | [
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17 | Dynamically Instance-Guided Adaptation: A Backward-Free Approach for Test-Time Domain Adaptive Semantic Segmentation | [
"Wei Wang",
"Zhun Zhong",
"Weijie Wang",
"Xi Chen",
"Charles Ling",
"Boyu Wang",
"Nicu Sebe"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wang_Dynamically_Instance-Guided_Adaptation_A_Backward-Free_Approach_for_Test-Time_Domain_Adaptive_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wang_Dynamically_Instance-Guided_Adaptation_A_Backward-Free_Approach_for_Test-Time_Domain_Adaptive_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Wang_Dynamically_Instance-Guided_Adaptation_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Wang_2023_CVPR,
author = {Wang, Wei and Zhong, Zhun and Wang, Weijie and Chen, Xi and Ling, Charles and Wang, Boyu and Sebe, Nicu},
title = {Dynamically Instance-Guided Adaptation: A Backward-Free Approach for Test-Time Domain Adaptive Semantic Segmentation},
booktitle = {Proceedings o... | In this paper, we study the application of Test-time domain adaptation in semantic segmentation (TTDA-Seg) where both efficiency and effectiveness are crucial. Existing methods either have low efficiency (e.g., backward optimization) or ignore semantic adaptation (e.g., distribution alignment). Besides, they would suff... | [
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18 | Painting 3D Nature in 2D: View Synthesis of Natural Scenes From a Single Semantic Mask | [
"Shangzhan Zhang",
"Sida Peng",
"Tianrun Chen",
"Linzhan Mou",
"Haotong Lin",
"Kaicheng Yu",
"Yiyi Liao",
"Xiaowei Zhou"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_Painting_3D_Nature_in_2D_View_Synthesis_of_Natural_Scenes_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Painting_3D_Nature_in_2D_View_Synthesis_of_Natural_Scenes_CVPR_2023_paper.pdf | null | 2302.07224 | cvf | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Shangzhan and Peng, Sida and Chen, Tianrun and Mou, Linzhan and Lin, Haotong and Yu, Kaicheng and Liao, Yiyi and Zhou, Xiaowei},
title = {Painting 3D Nature in 2D: View Synthesis of Natural Scenes From a Single Semantic Mask},
booktitle = {Proceedings ... | We introduce a novel approach that takes a single semantic mask as input to synthesize multi-view consistent color images of natural scenes, trained with a collection of single images from the Internet. Prior works on 3D-aware image synthesis either require multi-view supervision or learning category-level prior for sp... | [
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19 | LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data | [
"Jihye Park",
"Sunwoo Kim",
"Soohyun Kim",
"Seokju Cho",
"Jaejun Yoo",
"Youngjung Uh",
"Seungryong Kim"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Park_LANIT_Language-Driven_Image-to-Image_Translation_for_Unlabeled_Data_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Park_LANIT_Language-Driven_Image-to-Image_Translation_for_Unlabeled_Data_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Park_LANIT_Language-Driven_Image-to-Image_CVPR_2023_supplemental.pdf | 2208.14889 | cvf | @InProceedings{Park_2023_CVPR,
author = {Park, Jihye and Kim, Sunwoo and Kim, Soohyun and Cho, Seokju and Yoo, Jaejun and Uh, Youngjung and Kim, Seungryong},
title = {LANIT: Language-Driven Image-to-Image Translation for Unlabeled Data},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer... | Existing techniques for image-to-image translation commonly have suffered from two critical problems: heavy reliance on per-sample domain annotation and/or inability to handle multiple attributes per image. Recent truly-unsupervised methods adopt clustering approaches to easily provide per-sample one-hot domain labels.... | [
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20 | MoLo: Motion-Augmented Long-Short Contrastive Learning for Few-Shot Action Recognition | [
"Xiang Wang",
"Shiwei Zhang",
"Zhiwu Qing",
"Changxin Gao",
"Yingya Zhang",
"Deli Zhao",
"Nong Sang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wang_MoLo_Motion-Augmented_Long-Short_Contrastive_Learning_for_Few-Shot_Action_Recognition_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wang_MoLo_Motion-Augmented_Long-Short_Contrastive_Learning_for_Few-Shot_Action_Recognition_CVPR_2023_paper.pdf | null | 2304.00946 | cvf | @InProceedings{Wang_2023_CVPR,
author = {Wang, Xiang and Zhang, Shiwei and Qing, Zhiwu and Gao, Changxin and Zhang, Yingya and Zhao, Deli and Sang, Nong},
title = {MoLo: Motion-Augmented Long-Short Contrastive Learning for Few-Shot Action Recognition},
booktitle = {Proceedings of the IEEE/CVF Confere... | Current state-of-the-art approaches for few-shot action recognition achieve promising performance by conducting frame-level matching on learned visual features. However, they generally suffer from two limitations: i) the matching procedure between local frames tends to be inaccurate due to the lack of guidance to force... | [
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21 | Fast Point Cloud Generation With Straight Flows | [
"Lemeng Wu",
"Dilin Wang",
"Chengyue Gong",
"Xingchao Liu",
"Yunyang Xiong",
"Rakesh Ranjan",
"Raghuraman Krishnamoorthi",
"Vikas Chandra",
"Qiang Liu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wu_Fast_Point_Cloud_Generation_With_Straight_Flows_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wu_Fast_Point_Cloud_Generation_With_Straight_Flows_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Wu_Fast_Point_Cloud_CVPR_2023_supplemental.zip | 2212.01747 | cvf | @InProceedings{Wu_2023_CVPR,
author = {Wu, Lemeng and Wang, Dilin and Gong, Chengyue and Liu, Xingchao and Xiong, Yunyang and Ranjan, Rakesh and Krishnamoorthi, Raghuraman and Chandra, Vikas and Liu, Qiang},
title = {Fast Point Cloud Generation With Straight Flows},
booktitle = {Proceedings of the IE... | Diffusion models have emerged as a powerful tool for point cloud generation. A key component that drives the impressive performance for generating high-quality samples from noise is iteratively denoise for thousands of steps. While beneficial, the complexity of learning steps has limited its applications to many 3D rea... | [
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22 | Text-Guided Unsupervised Latent Transformation for Multi-Attribute Image Manipulation | [
"Xiwen Wei",
"Zhen Xu",
"Cheng Liu",
"Si Wu",
"Zhiwen Yu",
"Hau San Wong"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wei_Text-Guided_Unsupervised_Latent_Transformation_for_Multi-Attribute_Image_Manipulation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wei_Text-Guided_Unsupervised_Latent_Transformation_for_Multi-Attribute_Image_Manipulation_CVPR_2023_paper.pdf | null | null | null | @InProceedings{Wei_2023_CVPR,
author = {Wei, Xiwen and Xu, Zhen and Liu, Cheng and Wu, Si and Yu, Zhiwen and Wong, Hau San},
title = {Text-Guided Unsupervised Latent Transformation for Multi-Attribute Image Manipulation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patt... | Great progress has been made in StyleGAN-based image editing. To associate with preset attributes, most existing approaches focus on supervised learning for semantically meaningful latent space traversal directions, and each manipulation step is typically determined for an individual attribute. To address this limitati... | [
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23 | Achieving a Better Stability-Plasticity Trade-Off via Auxiliary Networks in Continual Learning | [
"Sanghwan Kim",
"Lorenzo Noci",
"Antonio Orvieto",
"Thomas Hofmann"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Kim_Achieving_a_Better_Stability-Plasticity_Trade-Off_via_Auxiliary_Networks_in_Continual_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Kim_Achieving_a_Better_Stability-Plasticity_Trade-Off_via_Auxiliary_Networks_in_Continual_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Kim_Achieving_a_Better_CVPR_2023_supplemental.pdf | 2303.09483 | cvf | @InProceedings{Kim_2023_CVPR,
author = {Kim, Sanghwan and Noci, Lorenzo and Orvieto, Antonio and Hofmann, Thomas},
title = {Achieving a Better Stability-Plasticity Trade-Off via Auxiliary Networks in Continual Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patte... | In contrast to the natural capabilities of humans to learn new tasks in a sequential fashion, neural networks are known to suffer from catastrophic forgetting, where the model's performances on old tasks drop dramatically after being optimized for a new task. Since then, the continual learning (CL) community has propos... | [
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24 | Power Bundle Adjustment for Large-Scale 3D Reconstruction | [
"Simon Weber",
"Nikolaus Demmel",
"Tin Chon Chan",
"Daniel Cremers"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Weber_Power_Bundle_Adjustment_for_Large-Scale_3D_Reconstruction_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Weber_Power_Bundle_Adjustment_for_Large-Scale_3D_Reconstruction_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Weber_Power_Bundle_Adjustment_CVPR_2023_supplemental.pdf | 2204.12834 | cvf | @InProceedings{Weber_2023_CVPR,
author = {Weber, Simon and Demmel, Nikolaus and Chan, Tin Chon and Cremers, Daniel},
title = {Power Bundle Adjustment for Large-Scale 3D Reconstruction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | We introduce Power Bundle Adjustment as an expansion type algorithm for solving large-scale bundle adjustment problems. It is based on the power series expansion of the inverse Schur complement and constitutes a new family of solvers that we call inverse expansion methods. We theoretically justify the use of power seri... | [
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25 | Picture That Sketch: Photorealistic Image Generation From Abstract Sketches | [
"Subhadeep Koley",
"Ayan Kumar Bhunia",
"Aneeshan Sain",
"Pinaki Nath Chowdhury",
"Tao Xiang",
"Yi-Zhe Song"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Koley_Picture_That_Sketch_Photorealistic_Image_Generation_From_Abstract_Sketches_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Koley_Picture_That_Sketch_Photorealistic_Image_Generation_From_Abstract_Sketches_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Koley_Picture_That_Sketch_CVPR_2023_supplemental.pdf | 2303.11162 | cvf | @InProceedings{Koley_2023_CVPR,
author = {Koley, Subhadeep and Bhunia, Ayan Kumar and Sain, Aneeshan and Chowdhury, Pinaki Nath and Xiang, Tao and Song, Yi-Zhe},
title = {Picture That Sketch: Photorealistic Image Generation From Abstract Sketches},
booktitle = {Proceedings of the IEEE/CVF Conference ... | Given an abstract, deformed, ordinary sketch from untrained amateurs like you and me, this paper turns it into a photorealistic image - just like those shown in Fig. 1(a), all non-cherry-picked. We differ significantly from prior art in that we do not dictate an edgemap-like sketch to start with, but aim to work with a... | [
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26 | Contrastive Semi-Supervised Learning for Underwater Image Restoration via Reliable Bank | [
"Shirui Huang",
"Keyan Wang",
"Huan Liu",
"Jun Chen",
"Yunsong Li"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Huang_Contrastive_Semi-Supervised_Learning_for_Underwater_Image_Restoration_via_Reliable_Bank_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Huang_Contrastive_Semi-Supervised_Learning_for_Underwater_Image_Restoration_via_Reliable_Bank_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Huang_Contrastive_Semi-Supervised_Learning_CVPR_2023_supplemental.pdf | 2303.09101 | cvf | @InProceedings{Huang_2023_CVPR,
author = {Huang, Shirui and Wang, Keyan and Liu, Huan and Chen, Jun and Li, Yunsong},
title = {Contrastive Semi-Supervised Learning for Underwater Image Restoration via Reliable Bank},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern R... | Despite the remarkable achievement of recent underwater image restoration techniques, the lack of labeled data has become a major hurdle for further progress. In this work, we propose a mean-teacher based Semi-supervised Underwater Image Restoration (Semi-UIR) framework to incorporate the unlabeled data into network tr... | [
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27 | Video Event Restoration Based on Keyframes for Video Anomaly Detection | [
"Zhiwei Yang",
"Jing Liu",
"Zhaoyang Wu",
"Peng Wu",
"Xiaotao Liu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yang_Video_Event_Restoration_Based_on_Keyframes_for_Video_Anomaly_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_Video_Event_Restoration_Based_on_Keyframes_for_Video_Anomaly_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Yang_Video_Event_Restoration_CVPR_2023_supplemental.pdf | 2304.05112 | cvf | @InProceedings{Yang_2023_CVPR,
author = {Yang, Zhiwei and Liu, Jing and Wu, Zhaoyang and Wu, Peng and Liu, Xiaotao},
title = {Video Event Restoration Based on Keyframes for Video Anomaly Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}... | Video anomaly detection (VAD) is a significant computer vision problem. Existing deep neural network (DNN) based VAD methods mostly follow the route of frame reconstruction or frame prediction. However, the lack of mining and learning of higher-level visual features and temporal context relationships in videos limits t... | [
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28 | EcoTTA: Memory-Efficient Continual Test-Time Adaptation via Self-Distilled Regularization | [
"Junha Song",
"Jungsoo Lee",
"In So Kweon",
"Sungha Choi"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Song_EcoTTA_Memory-Efficient_Continual_Test-Time_Adaptation_via_Self-Distilled_Regularization_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Song_EcoTTA_Memory-Efficient_Continual_Test-Time_Adaptation_via_Self-Distilled_Regularization_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Song_EcoTTA_Memory-Efficient_Continual_CVPR_2023_supplemental.pdf | 2303.01904 | cvf | @InProceedings{Song_2023_CVPR,
author = {Song, Junha and Lee, Jungsoo and Kweon, In So and Choi, Sungha},
title = {EcoTTA: Memory-Efficient Continual Test-Time Adaptation via Self-Distilled Regularization},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition... | This paper presents a simple yet effective approach that improves continual test-time adaptation (TTA) in a memory-efficient manner. TTA may primarily be conducted on edge devices with limited memory, so reducing memory is crucial but has been overlooked in previous TTA studies. In addition, long-term adaptation often ... | [
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29 | 3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification | [
"Jiazhao Zhang",
"Liu Dai",
"Fanpeng Meng",
"Qingnan Fan",
"Xuelin Chen",
"Kai Xu",
"He Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_3D-Aware_Object_Goal_Navigation_via_Simultaneous_Exploration_and_Identification_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_3D-Aware_Object_Goal_Navigation_via_Simultaneous_Exploration_and_Identification_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhang_3D-Aware_Object_Goal_CVPR_2023_supplemental.pdf | 2212.00338 | cvf | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Jiazhao and Dai, Liu and Meng, Fanpeng and Fan, Qingnan and Chen, Xuelin and Xu, Kai and Wang, He},
title = {3D-Aware Object Goal Navigation via Simultaneous Exploration and Identification},
booktitle = {Proceedings of the IEEE/CVF Conference on Comput... | Object goal navigation (ObjectNav) in unseen environments is a fundamental task for Embodied AI. Agents in existing works learn ObjectNav policies based on 2D maps, scene graphs, or image sequences. Considering this task happens in 3D space, a 3D-aware agent can advance its ObjectNav capability via learning from fine-g... | [
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30 | Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction | [
"Yuanhui Huang",
"Wenzhao Zheng",
"Yunpeng Zhang",
"Jie Zhou",
"Jiwen Lu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Huang_Tri-Perspective_View_for_Vision-Based_3D_Semantic_Occupancy_Prediction_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Huang_Tri-Perspective_View_for_Vision-Based_3D_Semantic_Occupancy_Prediction_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Huang_Tri-Perspective_View_for_CVPR_2023_supplemental.pdf | 2302.07817 | cvf | @InProceedings{Huang_2023_CVPR,
author = {Huang, Yuanhui and Zheng, Wenzhao and Zhang, Yunpeng and Zhou, Jie and Lu, Jiwen},
title = {Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition... | Modern methods for vision-centric autonomous driving perception widely adopt the bird's-eye-view (BEV) representation to describe a 3D scene. Despite its better efficiency than voxel representation, it has difficulty describing the fine-grained 3D structure of a scene with a single plane. To address this, we propose a ... | [
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31 | Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference | [
"Haoran You",
"Yunyang Xiong",
"Xiaoliang Dai",
"Bichen Wu",
"Peizhao Zhang",
"Haoqi Fan",
"Peter Vajda",
"Yingyan (Celine) Lin"
] | https://openaccess.thecvf.com/content/CVPR2023/html/You_Castling-ViT_Compressing_Self-Attention_via_Switching_Towards_Linear-Angular_Attention_at_Vision_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/You_Castling-ViT_Compressing_Self-Attention_via_Switching_Towards_Linear-Angular_Attention_at_Vision_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/You_Castling-ViT_Compressing_Self-Attention_CVPR_2023_supplemental.pdf | 2211.10526 | title_snapshot | @InProceedings{You_2023_CVPR,
author = {You, Haoran and Xiong, Yunyang and Dai, Xiaoliang and Wu, Bichen and Zhang, Peizhao and Fan, Haoqi and Vajda, Peter and Lin, Yingyan (Celine)},
title = {Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer In... | Vision Transformers (ViTs) have shown impressive performance but still require a high computation cost as compared to convolutional neural networks (CNNs), one reason is that ViTs' attention measures global similarities and thus has a quadratic complexity with the number of input tokens. Existing efficient ViTs adopt l... | [
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32 | Shape, Pose, and Appearance From a Single Image via Bootstrapped Radiance Field Inversion | [
"Dario Pavllo",
"David Joseph Tan",
"Marie-Julie Rakotosaona",
"Federico Tombari"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Pavllo_Shape_Pose_and_Appearance_From_a_Single_Image_via_Bootstrapped_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Pavllo_Shape_Pose_and_Appearance_From_a_Single_Image_via_Bootstrapped_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Pavllo_Shape_Pose_and_CVPR_2023_supplemental.zip | 2211.11674 | cvf | @InProceedings{Pavllo_2023_CVPR,
author = {Pavllo, Dario and Tan, David Joseph and Rakotosaona, Marie-Julie and Tombari, Federico},
title = {Shape, Pose, and Appearance From a Single Image via Bootstrapped Radiance Field Inversion},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Visi... | Neural Radiance Fields (NeRF) coupled with GANs represent a promising direction in the area of 3D reconstruction from a single view, owing to their ability to efficiently model arbitrary topologies. Recent work in this area, however, has mostly focused on synthetic datasets where exact ground-truth poses are known, and... | [
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33 | Unlearnable Clusters: Towards Label-Agnostic Unlearnable Examples | [
"Jiaming Zhang",
"Xingjun Ma",
"Qi Yi",
"Jitao Sang",
"Yu-Gang Jiang",
"Yaowei Wang",
"Changsheng Xu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_Unlearnable_Clusters_Towards_Label-Agnostic_Unlearnable_Examples_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Unlearnable_Clusters_Towards_Label-Agnostic_Unlearnable_Examples_CVPR_2023_paper.pdf | null | 2301.01217 | cvf | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Jiaming and Ma, Xingjun and Yi, Qi and Sang, Jitao and Jiang, Yu-Gang and Wang, Yaowei and Xu, Changsheng},
title = {Unlearnable Clusters: Towards Label-Agnostic Unlearnable Examples},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vis... | There is a growing interest in developing unlearnable examples (UEs) against visual privacy leaks on the Internet. UEs are training samples added with invisible but unlearnable noise, which have been found can prevent unauthorized training of machine learning models. UEs typically are generated via a bilevel optimizati... | [
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34 | Rethinking Federated Learning With Domain Shift: A Prototype View | [
"Wenke Huang",
"Mang Ye",
"Zekun Shi",
"He Li",
"Bo Du"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Huang_Rethinking_Federated_Learning_With_Domain_Shift_A_Prototype_View_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Huang_Rethinking_Federated_Learning_With_Domain_Shift_A_Prototype_View_CVPR_2023_paper.pdf | null | null | null | @InProceedings{Huang_2023_CVPR,
author = {Huang, Wenke and Ye, Mang and Shi, Zekun and Li, He and Du, Bo},
title = {Rethinking Federated Learning With Domain Shift: A Prototype View},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | Federated learning shows a bright promise as a privacy-preserving collaborative learning technique. However, prevalent solutions mainly focus on all private data sampled from the same domain. An important challenge is that when distributed data are derived from diverse domains. The private model presents degenerative p... | [
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35 | NoPe-NeRF: Optimising Neural Radiance Field With No Pose Prior | [
"Wenjing Bian",
"Zirui Wang",
"Kejie Li",
"Jia-Wang Bian",
"Victor Adrian Prisacariu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Bian_NoPe-NeRF_Optimising_Neural_Radiance_Field_With_No_Pose_Prior_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Bian_NoPe-NeRF_Optimising_Neural_Radiance_Field_With_No_Pose_Prior_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Bian_NoPe-NeRF_Optimising_Neural_CVPR_2023_supplemental.pdf | 2212.07388 | title_snapshot | @InProceedings{Bian_2023_CVPR,
author = {Bian, Wenjing and Wang, Zirui and Li, Kejie and Bian, Jia-Wang and Prisacariu, Victor Adrian},
title = {NoPe-NeRF: Optimising Neural Radiance Field With No Pose Prior},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognit... | Training a Neural Radiance Field (NeRF) without pre-computed camera poses is challenging. Recent advances in this direction demonstrate the possibility of jointly optimising a NeRF and camera poses in forward-facing scenes. However, these methods still face difficulties during dramatic camera movement. We tackle this c... | [
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36 | HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation | [
"Jian Ding",
"Nan Xue",
"Gui-Song Xia",
"Bernt Schiele",
"Dengxin Dai"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ding_HGFormer_Hierarchical_Grouping_Transformer_for_Domain_Generalized_Semantic_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ding_HGFormer_Hierarchical_Grouping_Transformer_for_Domain_Generalized_Semantic_Segmentation_CVPR_2023_paper.pdf | null | 2305.13031 | cvf | @InProceedings{Ding_2023_CVPR,
author = {Ding, Jian and Xue, Nan and Xia, Gui-Song and Schiele, Bernt and Dai, Dengxin},
title = {HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patte... | Current semantic segmentation models have achieved great success under the independent and identically distributed (i.i.d.) condition. However, in real-world applications, test data might come from a different domain than training data. Therefore, it is important to improve model robustness against domain differences. ... | [
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37 | Distilling Vision-Language Pre-Training To Collaborate With Weakly-Supervised Temporal Action Localization | [
"Chen Ju",
"Kunhao Zheng",
"Jinxiang Liu",
"Peisen Zhao",
"Ya Zhang",
"Jianlong Chang",
"Qi Tian",
"Yanfeng Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ju_Distilling_Vision-Language_Pre-Training_To_Collaborate_With_Weakly-Supervised_Temporal_Action_Localization_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ju_Distilling_Vision-Language_Pre-Training_To_Collaborate_With_Weakly-Supervised_Temporal_Action_Localization_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Ju_Distilling_Vision-Language_Pre-Training_CVPR_2023_supplemental.pdf | 2212.09335 | cvf | @InProceedings{Ju_2023_CVPR,
author = {Ju, Chen and Zheng, Kunhao and Liu, Jinxiang and Zhao, Peisen and Zhang, Ya and Chang, Jianlong and Tian, Qi and Wang, Yanfeng},
title = {Distilling Vision-Language Pre-Training To Collaborate With Weakly-Supervised Temporal Action Localization},
booktitle = {Pr... | Weakly-supervised temporal action localization (WTAL) learns to detect and classify action instances with only category labels. Most methods widely adopt the off-the-shelf Classification-Based Pre-training (CBP) to generate video features for action localization. However, the different optimization objectives between c... | [
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38 | Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised Semantic Segmentation | [
"Zhen Zhao",
"Lihe Yang",
"Sifan Long",
"Jimin Pi",
"Luping Zhou",
"Jingdong Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhao_Augmentation_Matters_A_Simple-Yet-Effective_Approach_to_Semi-Supervised_Semantic_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhao_Augmentation_Matters_A_Simple-Yet-Effective_Approach_to_Semi-Supervised_Semantic_Segmentation_CVPR_2023_paper.pdf | null | 2212.04976 | cvf | @InProceedings{Zhao_2023_CVPR,
author = {Zhao, Zhen and Yang, Lihe and Long, Sifan and Pi, Jimin and Zhou, Luping and Wang, Jingdong},
title = {Augmentation Matters: A Simple-Yet-Effective Approach to Semi-Supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Compu... | Recent studies on semi-supervised semantic segmentation (SSS) have seen fast progress. Despite their promising performance, current state-of-the-art methods tend to increasingly complex designs at the cost of introducing more network components and additional training procedures. Differently, in this work, we follow a ... | [
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39 | SIEDOB: Semantic Image Editing by Disentangling Object and Background | [
"Wuyang Luo",
"Su Yang",
"Xinjian Zhang",
"Weishan Zhang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Luo_SIEDOB_Semantic_Image_Editing_by_Disentangling_Object_and_Background_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Luo_SIEDOB_Semantic_Image_Editing_by_Disentangling_Object_and_Background_CVPR_2023_paper.pdf | null | 2303.13062 | cvf | @InProceedings{Luo_2023_CVPR,
author = {Luo, Wuyang and Yang, Su and Zhang, Xinjian and Zhang, Weishan},
title = {SIEDOB: Semantic Image Editing by Disentangling Object and Background},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | Semantic image editing provides users with a flexible tool to modify a given image guided by a corresponding segmentation map. In this task, the features of the foreground objects and the backgrounds are quite different. However, all previous methods handle backgrounds and objects as a whole using a monolithic model. C... | [
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40 | Multiclass Confidence and Localization Calibration for Object Detection | [
"Bimsara Pathiraja",
"Malitha Gunawardhana",
"Muhammad Haris Khan"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Pathiraja_Multiclass_Confidence_and_Localization_Calibration_for_Object_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Pathiraja_Multiclass_Confidence_and_Localization_Calibration_for_Object_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Pathiraja_Multiclass_Confidence_and_CVPR_2023_supplemental.pdf | 2306.08271 | title_snapshot | @InProceedings{Pathiraja_2023_CVPR,
author = {Pathiraja, Bimsara and Gunawardhana, Malitha and Khan, Muhammad Haris},
title = {Multiclass Confidence and Localization Calibration for Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR... | Albeit achieving high predictive accuracy across many challenging computer vision problems, recent studies suggest that deep neural networks (DNNs) tend to make overconfident predictions, rendering them poorly calibrated. Most of the existing attempts for improving DNN calibration are limited to classification tasks an... | [
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41 | Query-Dependent Video Representation for Moment Retrieval and Highlight Detection | [
"WonJun Moon",
"Sangeek Hyun",
"SangUk Park",
"Dongchan Park",
"Jae-Pil Heo"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Moon_Query-Dependent_Video_Representation_for_Moment_Retrieval_and_Highlight_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Moon_Query-Dependent_Video_Representation_for_Moment_Retrieval_and_Highlight_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Moon_Query-Dependent_Video_Representation_CVPR_2023_supplemental.pdf | 2303.13874 | cvf | @InProceedings{Moon_2023_CVPR,
author = {Moon, WonJun and Hyun, Sangeek and Park, SangUk and Park, Dongchan and Heo, Jae-Pil},
title = {Query-Dependent Video Representation for Moment Retrieval and Highlight Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patter... | Recently, video moment retrieval and highlight detection (MR/HD) are being spotlighted as the demand for video understanding is drastically increased. The key objective of MR/HD is to localize the moment and estimate clip-wise accordance level, i.e., saliency score, to the given text query. Although the recent transfor... | [
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42 | Robust 3D Shape Classification via Non-Local Graph Attention Network | [
"Shengwei Qin",
"Zhong Li",
"Ligang Liu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Qin_Robust_3D_Shape_Classification_via_Non-Local_Graph_Attention_Network_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Qin_Robust_3D_Shape_Classification_via_Non-Local_Graph_Attention_Network_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Qin_Robust_3D_Shape_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Qin_2023_CVPR,
author = {Qin, Shengwei and Li, Zhong and Liu, Ligang},
title = {Robust 3D Shape Classification via Non-Local Graph Attention Network},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
yea... | We introduce a non-local graph attention network (NLGAT), which generates a novel global descriptor through two sub-networks for robust 3D shape classification. In the first sub-network, we capture the global relationships between points (i.e., point-point features) by designing a global relationship network (GRN). In ... | [
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43 | Boosting Verified Training for Robust Image Classifications via Abstraction | [
"Zhaodi Zhang",
"Zhiyi Xue",
"Yang Chen",
"Si Liu",
"Yueling Zhang",
"Jing Liu",
"Min Zhang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_Boosting_Verified_Training_for_Robust_Image_Classifications_via_Abstraction_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Boosting_Verified_Training_for_Robust_Image_Classifications_via_Abstraction_CVPR_2023_paper.pdf | null | 2303.11552 | cvf | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Zhaodi and Xue, Zhiyi and Chen, Yang and Liu, Si and Zhang, Yueling and Liu, Jing and Zhang, Min},
title = {Boosting Verified Training for Robust Image Classifications via Abstraction},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vi... | This paper proposes a novel, abstraction-based, certified training method for robust image classifiers. Via abstraction, all perturbed images are mapped into intervals before feeding into neural networks for training. By training on intervals, all the perturbed images that are mapped to the same interval are classified... | [
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44 | Exploring Structured Semantic Prior for Multi Label Recognition With Incomplete Labels | [
"Zixuan Ding",
"Ao Wang",
"Hui Chen",
"Qiang Zhang",
"Pengzhang Liu",
"Yongjun Bao",
"Weipeng Yan",
"Jungong Han"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ding_Exploring_Structured_Semantic_Prior_for_Multi_Label_Recognition_With_Incomplete_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ding_Exploring_Structured_Semantic_Prior_for_Multi_Label_Recognition_With_Incomplete_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Ding_Exploring_Structured_Semantic_CVPR_2023_supplemental.pdf | 2303.13223 | cvf | @InProceedings{Ding_2023_CVPR,
author = {Ding, Zixuan and Wang, Ao and Chen, Hui and Zhang, Qiang and Liu, Pengzhang and Bao, Yongjun and Yan, Weipeng and Han, Jungong},
title = {Exploring Structured Semantic Prior for Multi Label Recognition With Incomplete Labels},
booktitle = {Proceedings of the I... | Multi-label recognition (MLR) with incomplete labels is very challenging. Recent works strive to explore the image-to-label correspondence in the vision-language model, i.e., CLIP, to compensate for insufficient annotations. In spite of promising performance, they generally overlook the valuable prior about the label-t... | [
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45 | Instance-Specific and Model-Adaptive Supervision for Semi-Supervised Semantic Segmentation | [
"Zhen Zhao",
"Sifan Long",
"Jimin Pi",
"Jingdong Wang",
"Luping Zhou"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhao_Instance-Specific_and_Model-Adaptive_Supervision_for_Semi-Supervised_Semantic_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhao_Instance-Specific_and_Model-Adaptive_Supervision_for_Semi-Supervised_Semantic_Segmentation_CVPR_2023_paper.pdf | null | 2211.11335 | cvf | @InProceedings{Zhao_2023_CVPR,
author = {Zhao, Zhen and Long, Sifan and Pi, Jimin and Wang, Jingdong and Zhou, Luping},
title = {Instance-Specific and Model-Adaptive Supervision for Semi-Supervised Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Patt... | Recently, semi-supervised semantic segmentation has achieved promising performance with a small fraction of labeled data. However, most existing studies treat all unlabeled data equally and barely consider the differences and training difficulties among unlabeled instances. Differentiating unlabeled instances can promo... | [
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46 | 3D Shape Reconstruction of Semi-Transparent Worms | [
"Thomas P. Ilett",
"Omer Yuval",
"Thomas Ranner",
"Netta Cohen",
"David C. Hogg"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ilett_3D_Shape_Reconstruction_of_Semi-Transparent_Worms_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ilett_3D_Shape_Reconstruction_of_Semi-Transparent_Worms_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Ilett_3D_Shape_Reconstruction_CVPR_2023_supplemental.pdf | 2304.14841 | cvf | @InProceedings{Ilett_2023_CVPR,
author = {Ilett, Thomas P. and Yuval, Omer and Ranner, Thomas and Cohen, Netta and Hogg, David C.},
title = {3D Shape Reconstruction of Semi-Transparent Worms},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
... | 3D shape reconstruction typically requires identifying object features or textures in multiple images of a subject. This approach is not viable when the subject is semi-transparent and moving in and out of focus. Here we overcome these challenges by rendering a candidate shape with adaptive blurring and transparency fo... | [
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47 | Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection With Single Point Supervision | [
"Xinyi Ying",
"Li Liu",
"Yingqian Wang",
"Ruojing Li",
"Nuo Chen",
"Zaiping Lin",
"Weidong Sheng",
"Shilin Zhou"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ying_Mapping_Degeneration_Meets_Label_Evolution_Learning_Infrared_Small_Target_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ying_Mapping_Degeneration_Meets_Label_Evolution_Learning_Infrared_Small_Target_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Ying_Mapping_Degeneration_Meets_CVPR_2023_supplemental.pdf | 2304.01484 | cvf | @InProceedings{Ying_2023_CVPR,
author = {Ying, Xinyi and Liu, Li and Wang, Yingqian and Li, Ruojing and Chen, Nuo and Lin, Zaiping and Sheng, Weidong and Zhou, Shilin},
title = {Mapping Degeneration Meets Label Evolution: Learning Infrared Small Target Detection With Single Point Supervision},
bookti... | Training a convolutional neural network (CNN) to detect infrared small targets in a fully supervised manner has gained remarkable research interests in recent years, but is highly labor expensive since a large number of per-pixel annotations are required. To handle this problem, in this paper, we make the first attempt... | [
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48 | Swept-Angle Synthetic Wavelength Interferometry | [
"Alankar Kotwal",
"Anat Levin",
"Ioannis Gkioulekas"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Kotwal_Swept-Angle_Synthetic_Wavelength_Interferometry_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Kotwal_Swept-Angle_Synthetic_Wavelength_Interferometry_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Kotwal_Swept-Angle_Synthetic_Wavelength_CVPR_2023_supplemental.pdf | 2205.10655 | cvf | @InProceedings{Kotwal_2023_CVPR,
author = {Kotwal, Alankar and Levin, Anat and Gkioulekas, Ioannis},
title = {Swept-Angle Synthetic Wavelength Interferometry},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | We present a new imaging technique, swept-angle synthetic wavelength interferometry, for full-field micron-scale 3D sensing. As in conventional synthetic wavelength interferometry, our technique uses light consisting of two narrowly-separated optical wavelengths, resulting in per-pixel interferometric measurements whos... | [
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49 | Delving Into Shape-Aware Zero-Shot Semantic Segmentation | [
"Xinyu Liu",
"Beiwen Tian",
"Zhen Wang",
"Rui Wang",
"Kehua Sheng",
"Bo Zhang",
"Hao Zhao",
"Guyue Zhou"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Liu_Delving_Into_Shape-Aware_Zero-Shot_Semantic_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Liu_Delving_Into_Shape-Aware_Zero-Shot_Semantic_Segmentation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Liu_Delving_Into_Shape-Aware_CVPR_2023_supplemental.pdf | 2304.08491 | cvf | @InProceedings{Liu_2023_CVPR,
author = {Liu, Xinyu and Tian, Beiwen and Wang, Zhen and Wang, Rui and Sheng, Kehua and Zhang, Bo and Zhao, Hao and Zhou, Guyue},
title = {Delving Into Shape-Aware Zero-Shot Semantic Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision an... | Thanks to the impressive progress of large-scale vision-language pretraining, recent recognition models can classify arbitrary objects in a zero-shot and open-set manner, with a surprisingly high accuracy. However, translating this success to semantic segmentation is not trivial, because this dense prediction task requ... | [
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50 | Post-Training Quantization on Diffusion Models | [
"Yuzhang Shang",
"Zhihang Yuan",
"Bin Xie",
"Bingzhe Wu",
"Yan Yan"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Shang_Post-Training_Quantization_on_Diffusion_Models_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Shang_Post-Training_Quantization_on_Diffusion_Models_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Shang_Post-Training_Quantization_on_CVPR_2023_supplemental.pdf | 2211.15736 | cvf | @InProceedings{Shang_2023_CVPR,
author = {Shang, Yuzhang and Yuan, Zhihang and Xie, Bin and Wu, Bingzhe and Yan, Yan},
title = {Post-Training Quantization on Diffusion Models},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {Jun... | Denoising diffusion (score-based) generative models have recently achieved significant accomplishments in generating realistic and diverse data. These approaches define a forward diffusion process for transforming data into noise and a backward denoising process for sampling data from noise. Unfortunately, the generati... | [
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51 | Adaptive Global Decay Process for Event Cameras | [
"Urbano Miguel Nunes",
"Ryad Benosman",
"Sio-Hoi Ieng"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Nunes_Adaptive_Global_Decay_Process_for_Event_Cameras_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Nunes_Adaptive_Global_Decay_Process_for_Event_Cameras_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Nunes_Adaptive_Global_Decay_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Nunes_2023_CVPR,
author = {Nunes, Urbano Miguel and Benosman, Ryad and Ieng, Sio-Hoi},
title = {Adaptive Global Decay Process for Event Cameras},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | In virtually all event-based vision problems, there is the need to select the most recent events, which are assumed to carry the most relevant information content. To achieve this, at least one of three main strategies is applied, namely: 1) constant temporal decay or fixed time window, 2) constant number of events, an... | [
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52 | Multi-Space Neural Radiance Fields | [
"Ze-Xin Yin",
"Jiaxiong Qiu",
"Ming-Ming Cheng",
"Bo Ren"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yin_Multi-Space_Neural_Radiance_Fields_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yin_Multi-Space_Neural_Radiance_Fields_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Yin_Multi-Space_Neural_Radiance_CVPR_2023_supplemental.pdf | 2305.04268 | cvf | @InProceedings{Yin_2023_CVPR,
author = {Yin, Ze-Xin and Qiu, Jiaxiong and Cheng, Ming-Ming and Ren, Bo},
title = {Multi-Space Neural Radiance Fields},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023}... | Neural Radiance Fields (NeRF) and its variants have reached state-of-the-art performance in many novel-view-synthesis-related tasks. However, current NeRF-based methods still suffer from the existence of reflective objects, often resulting in blurry or distorted rendering. Instead of calculating a single radiance field... | [
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53 | Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels | [
"Maria Sofia Bucarelli",
"Lucas Cassano",
"Federico Siciliano",
"Amin Mantrach",
"Fabrizio Silvestri"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Bucarelli_Leveraging_Inter-Rater_Agreement_for_Classification_in_the_Presence_of_Noisy_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Bucarelli_Leveraging_Inter-Rater_Agreement_for_Classification_in_the_Presence_of_Noisy_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Bucarelli_Leveraging_Inter-Rater_Agreement_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Bucarelli_2023_CVPR,
author = {Bucarelli, Maria Sofia and Cassano, Lucas and Siciliano, Federico and Mantrach, Amin and Silvestri, Fabrizio},
title = {Leveraging Inter-Rater Agreement for Classification in the Presence of Noisy Labels},
booktitle = {Proceedings of the IEEE/CVF Conferen... | In practical settings, classification datasets are obtained through a labelling process that is usually done by humans. Labels can be noisy as they are obtained by aggregating the different individual labels assigned to the same sample by multiple, and possibly disagreeing, annotators. The inter-rater agreement on thes... | [
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54 | Bitstream-Corrupted JPEG Images Are Restorable: Two-Stage Compensation and Alignment Framework for Image Restoration | [
"Wenyang Liu",
"Yi Wang",
"Kim-Hui Yap",
"Lap-Pui Chau"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Liu_Bitstream-Corrupted_JPEG_Images_Are_Restorable_Two-Stage_Compensation_and_Alignment_Framework_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Liu_Bitstream-Corrupted_JPEG_Images_Are_Restorable_Two-Stage_Compensation_and_Alignment_Framework_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Liu_Bitstream-Corrupted_JPEG_Images_CVPR_2023_supplemental.pdf | 2304.06976 | cvf | @InProceedings{Liu_2023_CVPR,
author = {Liu, Wenyang and Wang, Yi and Yap, Kim-Hui and Chau, Lap-Pui},
title = {Bitstream-Corrupted JPEG Images Are Restorable: Two-Stage Compensation and Alignment Framework for Image Restoration},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision... | In this paper, we study a real-world JPEG image restoration problem with bit errors on the encrypted bitstream. The bit errors bring unpredictable color casts and block shifts on decoded image contents, which cannot be trivially resolved by existing image restoration methods mainly relying on pre-defined degradation mo... | [
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55 | Analyzing Physical Impacts Using Transient Surface Wave Imaging | [
"Tianyuan Zhang",
"Mark Sheinin",
"Dorian Chan",
"Mark Rau",
"Matthew O’Toole",
"Srinivasa G. Narasimhan"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_Analyzing_Physical_Impacts_Using_Transient_Surface_Wave_Imaging_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_Analyzing_Physical_Impacts_Using_Transient_Surface_Wave_Imaging_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhang_Analyzing_Physical_Impacts_CVPR_2023_supplemental.zip | null | null | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Tianyuan and Sheinin, Mark and Chan, Dorian and Rau, Mark and O{\textquoteright}Toole, Matthew and Narasimhan, Srinivasa G.},
title = {Analyzing Physical Impacts Using Transient Surface Wave Imaging},
booktitle = {Proceedings of the IEEE/CVF Conference... | The subtle vibrations on an object's surface contain information about the object's physical properties and its interaction with the environment. Prior works imaged surface vibration to recover the object's material properties via modal analysis, which discards the transient vibrations propagating immediately after the... | [
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56 | X-Pruner: eXplainable Pruning for Vision Transformers | [
"Lu Yu",
"Wei Xiang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yu_X-Pruner_eXplainable_Pruning_for_Vision_Transformers_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yu_X-Pruner_eXplainable_Pruning_for_Vision_Transformers_CVPR_2023_paper.pdf | null | 2303.04935 | title_snapshot | @InProceedings{Yu_2023_CVPR,
author = {Yu, Lu and Xiang, Wei},
title = {X-Pruner: eXplainable Pruning for Vision Transformers},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
pages = {2435... | Recently vision transformer models have become prominent models for a range of tasks. These models, however, usually suffer from intensive computational costs and heavy memory requirements, making them impractical for deployment on edge platforms. Recent studies have proposed to prune transformers in an unexplainable m... | [
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57 | Hard Sample Matters a Lot in Zero-Shot Quantization | [
"Huantong Li",
"Xiangmiao Wu",
"Fanbing Lv",
"Daihai Liao",
"Thomas H. Li",
"Yonggang Zhang",
"Bo Han",
"Mingkui Tan"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_Hard_Sample_Matters_a_Lot_in_Zero-Shot_Quantization_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Hard_Sample_Matters_a_Lot_in_Zero-Shot_Quantization_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_Hard_Sample_Matters_CVPR_2023_supplemental.pdf | 2303.13826 | cvf | @InProceedings{Li_2023_CVPR,
author = {Li, Huantong and Wu, Xiangmiao and Lv, Fanbing and Liao, Daihai and Li, Thomas H. and Zhang, Yonggang and Han, Bo and Tan, Mingkui},
title = {Hard Sample Matters a Lot in Zero-Shot Quantization},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vi... | Zero-shot quantization (ZSQ) is promising for compressing and accelerating deep neural networks when the data for training full-precision models are inaccessible. In ZSQ, network quantization is performed using synthetic samples, thus, the performance of quantized models depends heavily on the quality of synthetic samp... | [
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58 | Meta Compositional Referring Expression Segmentation | [
"Li Xu",
"Mark He Huang",
"Xindi Shang",
"Zehuan Yuan",
"Ying Sun",
"Jun Liu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Xu_Meta_Compositional_Referring_Expression_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Xu_Meta_Compositional_Referring_Expression_Segmentation_CVPR_2023_paper.pdf | null | 2304.04415 | cvf | @InProceedings{Xu_2023_CVPR,
author = {Xu, Li and Huang, Mark He and Shang, Xindi and Yuan, Zehuan and Sun, Ying and Liu, Jun},
title = {Meta Compositional Referring Expression Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
m... | Referring expression segmentation aims to segment an object described by a language expression from an image. Despite the recent progress on this task, existing models tackling this task may not be able to fully capture semantics and visual representations of individual concepts, which limits their generalization capab... | [
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59 | Histopathology Whole Slide Image Analysis With Heterogeneous Graph Representation Learning | [
"Tsai Hor Chan",
"Fernando Julio Cendra",
"Lan Ma",
"Guosheng Yin",
"Lequan Yu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Chan_Histopathology_Whole_Slide_Image_Analysis_With_Heterogeneous_Graph_Representation_Learning_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Chan_Histopathology_Whole_Slide_Image_Analysis_With_Heterogeneous_Graph_Representation_Learning_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Chan_Histopathology_Whole_Slide_CVPR_2023_supplemental.pdf | 2307.04189 | title_snapshot | @InProceedings{Chan_2023_CVPR,
author = {Chan, Tsai Hor and Cendra, Fernando Julio and Ma, Lan and Yin, Guosheng and Yu, Lequan},
title = {Histopathology Whole Slide Image Analysis With Heterogeneous Graph Representation Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Visio... | Graph-based methods have been extensively applied to whole slide histopathology image (WSI) analysis due to the advantage of modeling the spatial relationships among different entities. However, most of the existing methods focus on modeling WSIs with homogeneous graphs (e.g., with homogeneous node type). Despite their... | [
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60 | ScanDMM: A Deep Markov Model of Scanpath Prediction for 360deg Images | [
"Xiangjie Sui",
"Yuming Fang",
"Hanwei Zhu",
"Shiqi Wang",
"Zhou Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Sui_ScanDMM_A_Deep_Markov_Model_of_Scanpath_Prediction_for_360deg_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Sui_ScanDMM_A_Deep_Markov_Model_of_Scanpath_Prediction_for_360deg_CVPR_2023_paper.pdf | null | null | null | @InProceedings{Sui_2023_CVPR,
author = {Sui, Xiangjie and Fang, Yuming and Zhu, Hanwei and Wang, Shiqi and Wang, Zhou},
title = {ScanDMM: A Deep Markov Model of Scanpath Prediction for 360deg Images},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR... | Scanpath prediction for 360deg images aims to produce dynamic gaze behaviors based on the human visual perception mechanism. Most existing scanpath prediction methods for 360deg images do not give a complete treatment of the time-dependency when predicting human scanpath, resulting in inferior performance and poor gene... | [
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61 | Towards All-in-One Pre-Training via Maximizing Multi-Modal Mutual Information | [
"Weijie Su",
"Xizhou Zhu",
"Chenxin Tao",
"Lewei Lu",
"Bin Li",
"Gao Huang",
"Yu Qiao",
"Xiaogang Wang",
"Jie Zhou",
"Jifeng Dai"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Su_Towards_All-in-One_Pre-Training_via_Maximizing_Multi-Modal_Mutual_Information_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Su_Towards_All-in-One_Pre-Training_via_Maximizing_Multi-Modal_Mutual_Information_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Su_Towards_All-in-One_Pre-Training_CVPR_2023_supplemental.pdf | 2211.09807 | cvf | @InProceedings{Su_2023_CVPR,
author = {Su, Weijie and Zhu, Xizhou and Tao, Chenxin and Lu, Lewei and Li, Bin and Huang, Gao and Qiao, Yu and Wang, Xiaogang and Zhou, Jie and Dai, Jifeng},
title = {Towards All-in-One Pre-Training via Maximizing Multi-Modal Mutual Information},
booktitle = {Proceedings... | To effectively exploit the potential of large-scale models, various pre-training strategies supported by massive data from different sources are proposed, including supervised pre-training, weakly-supervised pre-training, and self-supervised pre-training. It has been proved that combining multiple pre-training strategi... | [
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62 | Aligning Bag of Regions for Open-Vocabulary Object Detection | [
"Size Wu",
"Wenwei Zhang",
"Sheng Jin",
"Wentao Liu",
"Chen Change Loy"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wu_Aligning_Bag_of_Regions_for_Open-Vocabulary_Object_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wu_Aligning_Bag_of_Regions_for_Open-Vocabulary_Object_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Wu_Aligning_Bag_of_CVPR_2023_supplemental.pdf | 2302.13996 | cvf | @InProceedings{Wu_2023_CVPR,
author = {Wu, Size and Zhang, Wenwei and Jin, Sheng and Liu, Wentao and Loy, Chen Change},
title = {Aligning Bag of Regions for Open-Vocabulary Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
m... | Pre-trained vision-language models (VLMs) learn to align vision and language representations on large-scale datasets, where each image-text pair usually contains a bag of semantic concepts. However, existing open-vocabulary object detectors only align region embeddings individually with the corresponding features extra... | [
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63 | Two-View Geometry Scoring Without Correspondences | [
"Axel Barroso-Laguna",
"Eric Brachmann",
"Victor Adrian Prisacariu",
"Gabriel J. Brostow",
"Daniyar Turmukhambetov"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Barroso-Laguna_Two-View_Geometry_Scoring_Without_Correspondences_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Barroso-Laguna_Two-View_Geometry_Scoring_Without_Correspondences_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Barroso-Laguna_Two-View_Geometry_Scoring_CVPR_2023_supplemental.pdf | 2306.01596 | title_snapshot | @InProceedings{Barroso-Laguna_2023_CVPR,
author = {Barroso-Laguna, Axel and Brachmann, Eric and Prisacariu, Victor Adrian and Brostow, Gabriel J. and Turmukhambetov, Daniyar},
title = {Two-View Geometry Scoring Without Correspondences},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer ... | Camera pose estimation for two-view geometry traditionally relies on RANSAC. Normally, a multitude of image correspondences leads to a pool of proposed hypotheses, which are then scored to find a winning model. The inlier count is generally regarded as a reliable indicator of "consensus". We examine this scoring heuris... | [
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64 | Annealing-Based Label-Transfer Learning for Open World Object Detection | [
"Yuqing Ma",
"Hainan Li",
"Zhange Zhang",
"Jinyang Guo",
"Shanghang Zhang",
"Ruihao Gong",
"Xianglong Liu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Ma_Annealing-Based_Label-Transfer_Learning_for_Open_World_Object_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Ma_Annealing-Based_Label-Transfer_Learning_for_Open_World_Object_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Ma_Annealing-Based_Label-Transfer_Learning_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Ma_2023_CVPR,
author = {Ma, Yuqing and Li, Hainan and Zhang, Zhange and Guo, Jinyang and Zhang, Shanghang and Gong, Ruihao and Liu, Xianglong},
title = {Annealing-Based Label-Transfer Learning for Open World Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Comp... | Open world object detection (OWOD) has attracted extensive attention due to its practicability in the real world. Previous OWOD works manually designed unknown-discover strategies to select unknown proposals from the background, suffering from uncertainties without appropriate priors. In this paper, we claim the learni... | [
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65 | Continual Semantic Segmentation With Automatic Memory Sample Selection | [
"Lanyun Zhu",
"Tianrun Chen",
"Jianxiong Yin",
"Simon See",
"Jun Liu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhu_Continual_Semantic_Segmentation_With_Automatic_Memory_Sample_Selection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhu_Continual_Semantic_Segmentation_With_Automatic_Memory_Sample_Selection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhu_Continual_Semantic_Segmentation_CVPR_2023_supplemental.pdf | 2304.05015 | cvf | @InProceedings{Zhu_2023_CVPR,
author = {Zhu, Lanyun and Chen, Tianrun and Yin, Jianxiong and See, Simon and Liu, Jun},
title = {Continual Semantic Segmentation With Automatic Memory Sample Selection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR... | Continual Semantic Segmentation (CSS) extends static semantic segmentation by incrementally introducing new classes for training. To alleviate the catastrophic forgetting issue in CSS, a memory buffer that stores a small number of samples from the previous classes is constructed for replay. However, existing methods se... | [
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66 | Meta-Tuning Loss Functions and Data Augmentation for Few-Shot Object Detection | [
"Berkan Demirel",
"Orhun Buğra Baran",
"Ramazan Gokberk Cinbis"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Demirel_Meta-Tuning_Loss_Functions_and_Data_Augmentation_for_Few-Shot_Object_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Demirel_Meta-Tuning_Loss_Functions_and_Data_Augmentation_for_Few-Shot_Object_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Demirel_Meta-Tuning_Loss_Functions_CVPR_2023_supplemental.pdf | 2304.12161 | cvf | @InProceedings{Demirel_2023_CVPR,
author = {Demirel, Berkan and Baran, Orhun Bu\u{g}ra and Cinbis, Ramazan Gokberk},
title = {Meta-Tuning Loss Functions and Data Augmentation for Few-Shot Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition... | Few-shot object detection, the problem of modelling novel object detection categories with few training instances, is an emerging topic in the area of few-shot learning and object detection. Contemporary techniques can be divided into two groups: fine-tuning based and meta-learning based approaches. While meta-learning... | [
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67 | A Light Weight Model for Active Speaker Detection | [
"Junhua Liao",
"Haihan Duan",
"Kanghui Feng",
"Wanbing Zhao",
"Yanbing Yang",
"Liangyin Chen"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Liao_A_Light_Weight_Model_for_Active_Speaker_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Liao_A_Light_Weight_Model_for_Active_Speaker_Detection_CVPR_2023_paper.pdf | null | 2303.04439 | cvf | @InProceedings{Liao_2023_CVPR,
author = {Liao, Junhua and Duan, Haihan and Feng, Kanghui and Zhao, Wanbing and Yang, Yanbing and Chen, Liangyin},
title = {A Light Weight Model for Active Speaker Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition... | Active speaker detection is a challenging task in audio-visual scenarios, with the aim to detect who is speaking in one or more speaker scenarios. This task has received considerable attention because it is crucial in many applications. Existing studies have attempted to improve the performance by inputting multiple ca... | [
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68 | Self-Supervised Video Forensics by Audio-Visual Anomaly Detection | [
"Chao Feng",
"Ziyang Chen",
"Andrew Owens"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Feng_Self-Supervised_Video_Forensics_by_Audio-Visual_Anomaly_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Feng_Self-Supervised_Video_Forensics_by_Audio-Visual_Anomaly_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Feng_Self-Supervised_Video_Forensics_CVPR_2023_supplemental.pdf | 2301.01767 | cvf | @InProceedings{Feng_2023_CVPR,
author = {Feng, Chao and Chen, Ziyang and Owens, Andrew},
title = {Self-Supervised Video Forensics by Audio-Visual Anomaly Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
yea... | Manipulated videos often contain subtle inconsistencies between their visual and audio signals. We propose a video forensics method, based on anomaly detection, that can identify these inconsistencies, and that can be trained solely using real, unlabeled data. We train an autoregressive model to generate sequences of a... | [
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69 | CLIP2Scene: Towards Label-Efficient 3D Scene Understanding by CLIP | [
"Runnan Chen",
"Youquan Liu",
"Lingdong Kong",
"Xinge Zhu",
"Yuexin Ma",
"Yikang Li",
"Yuenan Hou",
"Yu Qiao",
"Wenping Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Chen_CLIP2Scene_Towards_Label-Efficient_3D_Scene_Understanding_by_CLIP_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Chen_CLIP2Scene_Towards_Label-Efficient_3D_Scene_Understanding_by_CLIP_CVPR_2023_paper.pdf | null | 2301.04926 | cvf | @InProceedings{Chen_2023_CVPR,
author = {Chen, Runnan and Liu, Youquan and Kong, Lingdong and Zhu, Xinge and Ma, Yuexin and Li, Yikang and Hou, Yuenan and Qiao, Yu and Wang, Wenping},
title = {CLIP2Scene: Towards Label-Efficient 3D Scene Understanding by CLIP},
booktitle = {Proceedings of the IEEE/CV... | Contrastive Language-Image Pre-training (CLIP) achieves promising results in 2D zero-shot and few-shot learning. Despite the impressive performance in 2D, applying CLIP to help the learning in 3D scene understanding has yet to be explored. In this paper, we make the first attempt to investigate how CLIP knowledge benef... | [
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70 | GCFAgg: Global and Cross-View Feature Aggregation for Multi-View Clustering | [
"Weiqing Yan",
"Yuanyang Zhang",
"Chenlei Lv",
"Chang Tang",
"Guanghui Yue",
"Liang Liao",
"Weisi Lin"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yan_GCFAgg_Global_and_Cross-View_Feature_Aggregation_for_Multi-View_Clustering_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yan_GCFAgg_Global_and_Cross-View_Feature_Aggregation_for_Multi-View_Clustering_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Yan_GCFAgg_Global_and_CVPR_2023_supplemental.pdf | 2305.06799 | cvf | @InProceedings{Yan_2023_CVPR,
author = {Yan, Weiqing and Zhang, Yuanyang and Lv, Chenlei and Tang, Chang and Yue, Guanghui and Liao, Liang and Lin, Weisi},
title = {GCFAgg: Global and Cross-View Feature Aggregation for Multi-View Clustering},
booktitle = {Proceedings of the IEEE/CVF Conference on Com... | Multi-view clustering can partition data samples into their categories by learning a consensus representation in unsupervised way and has received more and more attention in recent years. However, most existing deep clustering methods learn consensus representation or view-specific representations from multiple views v... | [
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71 | Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning | [
"Ming Li",
"Qingli Li",
"Yan Wang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_Class_Balanced_Adaptive_Pseudo_Labeling_for_Federated_Semi-Supervised_Learning_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Class_Balanced_Adaptive_Pseudo_Labeling_for_Federated_Semi-Supervised_Learning_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_Class_Balanced_Adaptive_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Li_2023_CVPR,
author = {Li, Ming and Li, Qingli and Wang, Yan},
title = {Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
... | This paper focuses on federated semi-supervised learning (FSSL), assuming that few clients have fully labeled data (labeled clients) and the training datasets in other clients are fully unlabeled (unlabeled clients). Existing methods attempt to deal with the challenges caused by not independent and identically distribu... | [
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72 | Rethinking Out-of-Distribution (OOD) Detection: Masked Image Modeling Is All You Need | [
"Jingyao Li",
"Pengguang Chen",
"Zexin He",
"Shaozuo Yu",
"Shu Liu",
"Jiaya Jia"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_Rethinking_Out-of-Distribution_OOD_Detection_Masked_Image_Modeling_Is_All_You_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Rethinking_Out-of-Distribution_OOD_Detection_Masked_Image_Modeling_Is_All_You_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_Rethinking_Out-of-Distribution_OOD_CVPR_2023_supplemental.pdf | 2302.02615 | cvf | @InProceedings{Li_2023_CVPR,
author = {Li, Jingyao and Chen, Pengguang and He, Zexin and Yu, Shaozuo and Liu, Shu and Jia, Jiaya},
title = {Rethinking Out-of-Distribution (OOD) Detection: Masked Image Modeling Is All You Need},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision an... | The core of out-of-distribution (OOD) detection is to learn the in-distribution (ID) representation, which is distinguishable from OOD samples. Previous work applied recognition-based methods to learn the ID features, which tend to learn shortcuts instead of comprehensive representations. In this work, we find surprisi... | [
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73 | DeGPR: Deep Guided Posterior Regularization for Multi-Class Cell Detection and Counting | [
"Aayush Kumar Tyagi",
"Chirag Mohapatra",
"Prasenjit Das",
"Govind Makharia",
"Lalita Mehra",
"Prathosh AP",
"Mausam"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Tyagi_DeGPR_Deep_Guided_Posterior_Regularization_for_Multi-Class_Cell_Detection_and_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Tyagi_DeGPR_Deep_Guided_Posterior_Regularization_for_Multi-Class_Cell_Detection_and_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Tyagi_DeGPR_Deep_Guided_CVPR_2023_supplemental.pdf | 2304.00741 | cvf | @InProceedings{Tyagi_2023_CVPR,
author = {Tyagi, Aayush Kumar and Mohapatra, Chirag and Das, Prasenjit and Makharia, Govind and Mehra, Lalita and AP, Prathosh and Mausam},
title = {DeGPR: Deep Guided Posterior Regularization for Multi-Class Cell Detection and Counting},
booktitle = {Proceedings of th... | Multi-class cell detection and counting is an essential task for many pathological diagnoses. Manual counting is tedious and often leads to inter-observer variations among pathologists. While there exist multiple, general-purpose, deep learning-based object detection and counting methods, they may not readily transfer ... | [
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74 | Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning | [
"Xiaoyang Wu",
"Xin Wen",
"Xihui Liu",
"Hengshuang Zhao"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Wu_Masked_Scene_Contrast_A_Scalable_Framework_for_Unsupervised_3D_Representation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Wu_Masked_Scene_Contrast_A_Scalable_Framework_for_Unsupervised_3D_Representation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Wu_Masked_Scene_Contrast_CVPR_2023_supplemental.pdf | 2303.14191 | cvf | @InProceedings{Wu_2023_CVPR,
author = {Wu, Xiaoyang and Wen, Xin and Liu, Xihui and Zhao, Hengshuang},
title = {Masked Scene Contrast: A Scalable Framework for Unsupervised 3D Representation Learning},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVP... | As a pioneering work, PointContrast conducts unsupervised 3D representation learning via leveraging contrastive learning over raw RGB-D frames and proves its effectiveness on various downstream tasks. However, the trend of large-scale unsupervised learning in 3D has yet to emerge due to two stumbling blocks: the ineffi... | [
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75 | Multi Domain Learning for Motion Magnification | [
"Jasdeep Singh",
"Subrahmanyam Murala",
"G. Sankara Raju Kosuru"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Singh_Multi_Domain_Learning_for_Motion_Magnification_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Singh_Multi_Domain_Learning_for_Motion_Magnification_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Singh_Multi_Domain_Learning_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Singh_2023_CVPR,
author = {Singh, Jasdeep and Murala, Subrahmanyam and Kosuru, G. Sankara Raju},
title = {Multi Domain Learning for Motion Magnification},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
... | Video motion magnification makes subtle invisible motions visible, such as small chest movements while breathing, subtle vibrations in the moving objects etc. But small motions are prone to noise, illumination changes, large motions, etc. making the task difficult. Most state-of-the-art methods use hand-crafted concept... | [
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76 | LOGO: A Long-Form Video Dataset for Group Action Quality Assessment | [
"Shiyi Zhang",
"Wenxun Dai",
"Sujia Wang",
"Xiangwei Shen",
"Jiwen Lu",
"Jie Zhou",
"Yansong Tang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_LOGO_A_Long-Form_Video_Dataset_for_Group_Action_Quality_Assessment_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_LOGO_A_Long-Form_Video_Dataset_for_Group_Action_Quality_Assessment_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhang_LOGO_A_Long-Form_CVPR_2023_supplemental.zip | 2404.05029 | title_snapshot | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Shiyi and Dai, Wenxun and Wang, Sujia and Shen, Xiangwei and Lu, Jiwen and Zhou, Jie and Tang, Yansong},
title = {LOGO: A Long-Form Video Dataset for Group Action Quality Assessment},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Visi... | Action quality assessment (AQA) has become an emerging topic since it can be extensively applied in numerous scenarios. However, most existing methods and datasets focus on single-person short-sequence scenes, hindering the application of AQA in more complex situations. To address this issue, we construct a new multi-p... | [
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77 | A Simple Baseline for Video Restoration With Grouped Spatial-Temporal Shift | [
"Dasong Li",
"Xiaoyu Shi",
"Yi Zhang",
"Ka Chun Cheung",
"Simon See",
"Xiaogang Wang",
"Hongwei Qin",
"Hongsheng Li"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_A_Simple_Baseline_for_Video_Restoration_With_Grouped_Spatial-Temporal_Shift_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_A_Simple_Baseline_for_Video_Restoration_With_Grouped_Spatial-Temporal_Shift_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_A_Simple_Baseline_CVPR_2023_supplemental.pdf | 2206.10810 | cvf | @InProceedings{Li_2023_CVPR,
author = {Li, Dasong and Shi, Xiaoyu and Zhang, Yi and Cheung, Ka Chun and See, Simon and Wang, Xiaogang and Qin, Hongwei and Li, Hongsheng},
title = {A Simple Baseline for Video Restoration With Grouped Spatial-Temporal Shift},
booktitle = {Proceedings of the IEEE/CVF Co... | Video restoration, which aims to restore clear frames from degraded videos, has numerous important applications. The key to video restoration depends on utilizing inter-frame information. However, existing deep learning methods often rely on complicated network architectures, such as optical flow estimation, deformable... | [
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78 | UniSim: A Neural Closed-Loop Sensor Simulator | [
"Ze Yang",
"Yun Chen",
"Jingkang Wang",
"Sivabalan Manivasagam",
"Wei-Chiu Ma",
"Anqi Joyce Yang",
"Raquel Urtasun"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yang_UniSim_A_Neural_Closed-Loop_Sensor_Simulator_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_UniSim_A_Neural_Closed-Loop_Sensor_Simulator_CVPR_2023_paper.pdf | null | 2308.01898 | title_snapshot | @InProceedings{Yang_2023_CVPR,
author = {Yang, Ze and Chen, Yun and Wang, Jingkang and Manivasagam, Sivabalan and Ma, Wei-Chiu and Yang, Anqi Joyce and Urtasun, Raquel},
title = {UniSim: A Neural Closed-Loop Sensor Simulator},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and... | Rigorously testing autonomy systems is essential for making safe self-driving vehicles (SDV) a reality. It requires one to generate safety critical scenarios beyond what can be collected safely in the world, as many scenarios happen rarely on our roads. To accurately evaluate performance, we need to test the SDV on the... | [
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79 | itKD: Interchange Transfer-Based Knowledge Distillation for 3D Object Detection | [
"Hyeon Cho",
"Junyong Choi",
"Geonwoo Baek",
"Wonjun Hwang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Cho_itKD_Interchange_Transfer-Based_Knowledge_Distillation_for_3D_Object_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Cho_itKD_Interchange_Transfer-Based_Knowledge_Distillation_for_3D_Object_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Cho_itKD_Interchange_Transfer-Based_CVPR_2023_supplemental.pdf | 2205.15531 | cvf | @InProceedings{Cho_2023_CVPR,
author = {Cho, Hyeon and Choi, Junyong and Baek, Geonwoo and Hwang, Wonjun},
title = {itKD: Interchange Transfer-Based Knowledge Distillation for 3D Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},... | Point-cloud based 3D object detectors recently have achieved remarkable progress. However, most studies are limited to the development of network architectures for improving only their accuracy without consideration of the computational efficiency. In this paper, we first propose an autoencoder-style framework comprisi... | [
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80 | SliceMatch: Geometry-Guided Aggregation for Cross-View Pose Estimation | [
"Ted Lentsch",
"Zimin Xia",
"Holger Caesar",
"Julian F. P. Kooij"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Lentsch_SliceMatch_Geometry-Guided_Aggregation_for_Cross-View_Pose_Estimation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Lentsch_SliceMatch_Geometry-Guided_Aggregation_for_Cross-View_Pose_Estimation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Lentsch_SliceMatch_Geometry-Guided_Aggregation_CVPR_2023_supplemental.pdf | 2211.14651 | cvf | @InProceedings{Lentsch_2023_CVPR,
author = {Lentsch, Ted and Xia, Zimin and Caesar, Holger and Kooij, Julian F. P.},
title = {SliceMatch: Geometry-Guided Aggregation for Cross-View Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}... | This work addresses cross-view camera pose estimation, i.e., determining the 3-Degrees-of-Freedom camera pose of a given ground-level image w.r.t. an aerial image of the local area. We propose SliceMatch, which consists of ground and aerial feature extractors, feature aggregators, and a pose predictor. The feature extr... | [
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81 | 2PCNet: Two-Phase Consistency Training for Day-to-Night Unsupervised Domain Adaptive Object Detection | [
"Mikhail Kennerley",
"Jian-Gang Wang",
"Bharadwaj Veeravalli",
"Robby T. Tan"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Kennerley_2PCNet_Two-Phase_Consistency_Training_for_Day-to-Night_Unsupervised_Domain_Adaptive_Object_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Kennerley_2PCNet_Two-Phase_Consistency_Training_for_Day-to-Night_Unsupervised_Domain_Adaptive_Object_CVPR_2023_paper.pdf | null | 2303.13853 | cvf | @InProceedings{Kennerley_2023_CVPR,
author = {Kennerley, Mikhail and Wang, Jian-Gang and Veeravalli, Bharadwaj and Tan, Robby T.},
title = {2PCNet: Two-Phase Consistency Training for Day-to-Night Unsupervised Domain Adaptive Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Co... | Object detection at night is a challenging problem due to the absence of night image annotations. Despite several domain adaptation methods, achieving high-precision results remains an issue. False-positive error propagation is still observed in methods using the well-established student-teacher framework, particularly... | [
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82 | Prefix Conditioning Unifies Language and Label Supervision | [
"Kuniaki Saito",
"Kihyuk Sohn",
"Xiang Zhang",
"Chun-Liang Li",
"Chen-Yu Lee",
"Kate Saenko",
"Tomas Pfister"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Saito_Prefix_Conditioning_Unifies_Language_and_Label_Supervision_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Saito_Prefix_Conditioning_Unifies_Language_and_Label_Supervision_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Saito_Prefix_Conditioning_Unifies_CVPR_2023_supplemental.pdf | 2206.01125 | cvf | @InProceedings{Saito_2023_CVPR,
author = {Saito, Kuniaki and Sohn, Kihyuk and Zhang, Xiang and Li, Chun-Liang and Lee, Chen-Yu and Saenko, Kate and Pfister, Tomas},
title = {Prefix Conditioning Unifies Language and Label Supervision},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vi... | Pretraining visual models on web-scale image-caption datasets has recently emerged as a powerful alternative to traditional pretraining on image classification data. Image-caption datasets are more "open-domain", containing broader scene types and vocabulary words, and result in models that have strong performance in f... | [
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83 | Panoptic Lifting for 3D Scene Understanding With Neural Fields | [
"Yawar Siddiqui",
"Lorenzo Porzi",
"Samuel Rota Bulò",
"Norman Müller",
"Matthias Nießner",
"Angela Dai",
"Peter Kontschieder"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Siddiqui_Panoptic_Lifting_for_3D_Scene_Understanding_With_Neural_Fields_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Siddiqui_Panoptic_Lifting_for_3D_Scene_Understanding_With_Neural_Fields_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Siddiqui_Panoptic_Lifting_for_CVPR_2023_supplemental.pdf | 2212.09802 | title_snapshot | @InProceedings{Siddiqui_2023_CVPR,
author = {Siddiqui, Yawar and Porzi, Lorenzo and Bul\`o, Samuel Rota and M\"uller, Norman and Nie{\ss}ner, Matthias and Dai, Angela and Kontschieder, Peter},
title = {Panoptic Lifting for 3D Scene Understanding With Neural Fields},
booktitle = {Proceedings of the IE... | We propose Panoptic Lifting, a novel approach for learning panoptic 3D volumetric representations from images of in-the-wild scenes. Once trained, our model can render color images together with 3D-consistent panoptic segmentation from novel viewpoints. Unlike existing approaches which use 3D input directly or indirect... | [
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84 | WeatherStream: Light Transport Automation of Single Image Deweathering | [
"Howard Zhang",
"Yunhao Ba",
"Ethan Yang",
"Varan Mehra",
"Blake Gella",
"Akira Suzuki",
"Arnold Pfahnl",
"Chethan Chinder Chandrappa",
"Alex Wong",
"Achuta Kadambi"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zhang_WeatherStream_Light_Transport_Automation_of_Single_Image_Deweathering_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_WeatherStream_Light_Transport_Automation_of_Single_Image_Deweathering_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Zhang_WeatherStream_Light_Transport_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Zhang_2023_CVPR,
author = {Zhang, Howard and Ba, Yunhao and Yang, Ethan and Mehra, Varan and Gella, Blake and Suzuki, Akira and Pfahnl, Arnold and Chandrappa, Chethan Chinder and Wong, Alex and Kadambi, Achuta},
title = {WeatherStream: Light Transport Automation of Single Image Deweatherin... | Today single image deweathering is arguably more sensitive to the dataset type, rather than the model. We introduce WeatherStream, an automatic pipeline capturing all real-world weather effects (rain, snow, and rain fog degradations), along with their clean image pairs. Previous state-of-the-art methods that have attem... | [
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85 | Learning To Detect Mirrors From Videos via Dual Correspondences | [
"Jiaying Lin",
"Xin Tan",
"Rynson W.H. Lau"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Lin_Learning_To_Detect_Mirrors_From_Videos_via_Dual_Correspondences_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Lin_Learning_To_Detect_Mirrors_From_Videos_via_Dual_Correspondences_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Lin_Learning_To_Detect_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Lin_2023_CVPR,
author = {Lin, Jiaying and Tan, Xin and Lau, Rynson W.H.},
title = {Learning To Detect Mirrors From Videos via Dual Correspondences},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year ... | Detecting mirrors from static images has received significant research interest recently. However, detecting mirrors over dynamic scenes is still under-explored due to the lack of a high-quality dataset and an effective method for video mirror detection (VMD). To the best of our knowledge, this is the first work to add... | [
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86 | Single View Scene Scale Estimation Using Scale Field | [
"Byeong-Uk Lee",
"Jianming Zhang",
"Yannick Hold-Geoffroy",
"In So Kweon"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Lee_Single_View_Scene_Scale_Estimation_Using_Scale_Field_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Lee_Single_View_Scene_Scale_Estimation_Using_Scale_Field_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Lee_Single_View_Scene_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Lee_2023_CVPR,
author = {Lee, Byeong-Uk and Zhang, Jianming and Hold-Geoffroy, Yannick and Kweon, In So},
title = {Single View Scene Scale Estimation Using Scale Field},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | In this paper, we propose a single image scale estimation method based on a novel scale field representation. A scale field defines the local pixel-to-metric conversion ratio along the gravity direction on all the ground pixels. This representation resolves the ambiguity in camera parameters, allowing us to use a simpl... | [
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87 | Learning Semantic-Aware Disentangled Representation for Flexible 3D Human Body Editing | [
"Xiaokun Sun",
"Qiao Feng",
"Xiongzheng Li",
"Jinsong Zhang",
"Yu-Kun Lai",
"Jingyu Yang",
"Kun Li"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Sun_Learning_Semantic-Aware_Disentangled_Representation_for_Flexible_3D_Human_Body_Editing_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Sun_Learning_Semantic-Aware_Disentangled_Representation_for_Flexible_3D_Human_Body_Editing_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Sun_Learning_Semantic-Aware_Disentangled_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Sun_2023_CVPR,
author = {Sun, Xiaokun and Feng, Qiao and Li, Xiongzheng and Zhang, Jinsong and Lai, Yu-Kun and Yang, Jingyu and Li, Kun},
title = {Learning Semantic-Aware Disentangled Representation for Flexible 3D Human Body Editing},
booktitle = {Proceedings of the IEEE/CVF Conferenc... | 3D human body representation learning has received increasing attention in recent years. However, existing works cannot flexibly, controllably and accurately represent human bodies, limited by coarse semantics and unsatisfactory representation capability, particularly in the absence of supervised data. In this paper, w... | [
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88 | Generating Features With Increased Crop-Related Diversity for Few-Shot Object Detection | [
"Jingyi Xu",
"Hieu Le",
"Dimitris Samaras"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Xu_Generating_Features_With_Increased_Crop-Related_Diversity_for_Few-Shot_Object_Detection_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Xu_Generating_Features_With_Increased_Crop-Related_Diversity_for_Few-Shot_Object_Detection_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Xu_Generating_Features_With_CVPR_2023_supplemental.pdf | 2304.05096 | cvf | @InProceedings{Xu_2023_CVPR,
author = {Xu, Jingyi and Le, Hieu and Samaras, Dimitris},
title = {Generating Features With Increased Crop-Related Diversity for Few-Shot Object Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | Two-stage object detectors generate object proposals and classify them to detect objects in images. These proposals often do not perfectly contain the objects but overlap with them in many possible ways, exhibiting great variability in the difficulty levels of the proposals. Training a robust classifier against this cr... | [
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89 | Towards Scalable Neural Representation for Diverse Videos | [
"Bo He",
"Xitong Yang",
"Hanyu Wang",
"Zuxuan Wu",
"Hao Chen",
"Shuaiyi Huang",
"Yixuan Ren",
"Ser-Nam Lim",
"Abhinav Shrivastava"
] | https://openaccess.thecvf.com/content/CVPR2023/html/He_Towards_Scalable_Neural_Representation_for_Diverse_Videos_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/He_Towards_Scalable_Neural_Representation_for_Diverse_Videos_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/He_Towards_Scalable_Neural_CVPR_2023_supplemental.pdf | 2303.14124 | cvf | @InProceedings{He_2023_CVPR,
author = {He, Bo and Yang, Xitong and Wang, Hanyu and Wu, Zuxuan and Chen, Hao and Huang, Shuaiyi and Ren, Yixuan and Lim, Ser-Nam and Shrivastava, Abhinav},
title = {Towards Scalable Neural Representation for Diverse Videos},
booktitle = {Proceedings of the IEEE/CVF Conf... | Implicit neural representations (INR) have gained increasing attention in representing 3D scenes and images, and have been recently applied to encode videos (e.g., NeRV, E-NeRV). While achieving promising results, existing INR-based methods are limited to encoding a handful of short videos (e.g., seven 5-second videos ... | [
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90 | The Devil Is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation | [
"Beomyoung Kim",
"Joonhyun Jeong",
"Dongyoon Han",
"Sung Ju Hwang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Kim_The_Devil_Is_in_the_Points_Weakly_Semi-Supervised_Instance_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Kim_The_Devil_Is_in_the_Points_Weakly_Semi-Supervised_Instance_Segmentation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Kim_The_Devil_Is_CVPR_2023_supplemental.pdf | 2303.15062 | cvf | @InProceedings{Kim_2023_CVPR,
author = {Kim, Beomyoung and Jeong, Joonhyun and Han, Dongyoon and Hwang, Sung Ju},
title = {The Devil Is in the Points: Weakly Semi-Supervised Instance Segmentation via Point-Guided Mask Representation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vi... | In this paper, we introduce a novel learning scheme named weakly semi-supervised instance segmentation (WSSIS) with point labels for budget-efficient and high-performance instance segmentation. Namely, we consider a dataset setting consisting of a few fully-labeled images and a lot of point-labeled images. Motivated by... | [
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91 | Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations | [
"Lei Hsiung",
"Yun-Yun Tsai",
"Pin-Yu Chen",
"Tsung-Yi Ho"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Hsiung_Towards_Compositional_Adversarial_Robustness_Generalizing_Adversarial_Training_to_Composite_Semantic_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Hsiung_Towards_Compositional_Adversarial_Robustness_Generalizing_Adversarial_Training_to_Composite_Semantic_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Hsiung_Towards_Compositional_Adversarial_CVPR_2023_supplemental.pdf | 2202.04235 | cvf | @InProceedings{Hsiung_2023_CVPR,
author = {Hsiung, Lei and Tsai, Yun-Yun and Chen, Pin-Yu and Ho, Tsung-Yi},
title = {Towards Compositional Adversarial Robustness: Generalizing Adversarial Training to Composite Semantic Perturbations},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer V... | Model robustness against adversarial examples of single perturbation type such as the Lp-norm has been widely studied, yet its generalization to more realistic scenarios involving multiple semantic perturbations and their composition remains largely unexplored. In this paper, we first propose a novel method for generat... | [
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92 | Language-Guided Audio-Visual Source Separation via Trimodal Consistency | [
"Reuben Tan",
"Arijit Ray",
"Andrea Burns",
"Bryan A. Plummer",
"Justin Salamon",
"Oriol Nieto",
"Bryan Russell",
"Kate Saenko"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Tan_Language-Guided_Audio-Visual_Source_Separation_via_Trimodal_Consistency_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Tan_Language-Guided_Audio-Visual_Source_Separation_via_Trimodal_Consistency_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Tan_Language-Guided_Audio-Visual_Source_CVPR_2023_supplemental.pdf | 2303.16342 | cvf | @InProceedings{Tan_2023_CVPR,
author = {Tan, Reuben and Ray, Arijit and Burns, Andrea and Plummer, Bryan A. and Salamon, Justin and Nieto, Oriol and Russell, Bryan and Saenko, Kate},
title = {Language-Guided Audio-Visual Source Separation via Trimodal Consistency},
booktitle = {Proceedings of the IEE... | We propose a self-supervised approach for learning to perform audio source separation in videos based on natural language queries, using only unlabeled video and audio pairs as training data. A key challenge in this task is learning to associate the linguistic description of a sound-emitting object to its visual featur... | [
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93 | CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition With Variational Alignment | [
"Jiangbin Zheng",
"Yile Wang",
"Cheng Tan",
"Siyuan Li",
"Ge Wang",
"Jun Xia",
"Yidong Chen",
"Stan Z. Li"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Zheng_CVT-SLR_Contrastive_Visual-Textual_Transformation_for_Sign_Language_Recognition_With_Variational_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Zheng_CVT-SLR_Contrastive_Visual-Textual_Transformation_for_Sign_Language_Recognition_With_Variational_CVPR_2023_paper.pdf | null | 2303.05725 | title_snapshot | @InProceedings{Zheng_2023_CVPR,
author = {Zheng, Jiangbin and Wang, Yile and Tan, Cheng and Li, Siyuan and Wang, Ge and Xia, Jun and Chen, Yidong and Li, Stan Z.},
title = {CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition With Variational Alignment},
booktitle = {Proce... | Sign language recognition (SLR) is a weakly supervised task that annotates sign videos as textual glosses. Recent studies show that insufficient training caused by the lack of large-scale available sign datasets becomes the main bottleneck for SLR. Most SLR works thereby adopt pretrained visual modules and develop two ... | [
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94 | DynaMask: Dynamic Mask Selection for Instance Segmentation | [
"Ruihuang Li",
"Chenhang He",
"Shuai Li",
"Yabin Zhang",
"Lei Zhang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_DynaMask_Dynamic_Mask_Selection_for_Instance_Segmentation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_DynaMask_Dynamic_Mask_Selection_for_Instance_Segmentation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_DynaMask_Dynamic_Mask_CVPR_2023_supplemental.pdf | 2303.07868 | cvf | @InProceedings{Li_2023_CVPR,
author = {Li, Ruihuang and He, Chenhang and Li, Shuai and Zhang, Yabin and Zhang, Lei},
title = {DynaMask: Dynamic Mask Selection for Instance Segmentation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month ... | The representative instance segmentation methods mostly segment different object instances with a mask of the fixed resolution, e.g., 28x 28 grid. However, a low-resolution mask loses rich details, while a high-resolution mask incurs quadratic computation overhead. It is a challenging task to predict the optimal binary... | [
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95 | Paint by Example: Exemplar-Based Image Editing With Diffusion Models | [
"Binxin Yang",
"Shuyang Gu",
"Bo Zhang",
"Ting Zhang",
"Xuejin Chen",
"Xiaoyan Sun",
"Dong Chen",
"Fang Wen"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yang_Paint_by_Example_Exemplar-Based_Image_Editing_With_Diffusion_Models_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_Paint_by_Example_Exemplar-Based_Image_Editing_With_Diffusion_Models_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Yang_Paint_by_Example_CVPR_2023_supplemental.pdf | 2211.13227 | cvf | @InProceedings{Yang_2023_CVPR,
author = {Yang, Binxin and Gu, Shuyang and Zhang, Bo and Zhang, Ting and Chen, Xuejin and Sun, Xiaoyan and Chen, Dong and Wen, Fang},
title = {Paint by Example: Exemplar-Based Image Editing With Diffusion Models},
booktitle = {Proceedings of the IEEE/CVF Conference on C... | Language-guided image editing has achieved great success recently. In this paper, we investigate exemplar-guided image editing for more precise control. We achieve this goal by leveraging self-supervised training to disentangle and re-organize the source image and the exemplar. However, the naive approach will cause ob... | [
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96 | Ego-Body Pose Estimation via Ego-Head Pose Estimation | [
"Jiaman Li",
"Karen Liu",
"Jiajun Wu"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Li_Ego-Body_Pose_Estimation_via_Ego-Head_Pose_Estimation_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Li_Ego-Body_Pose_Estimation_via_Ego-Head_Pose_Estimation_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Li_Ego-Body_Pose_Estimation_CVPR_2023_supplemental.pdf | 2212.04636 | cvf | @InProceedings{Li_2023_CVPR,
author = {Li, Jiaman and Liu, Karen and Wu, Jiajun},
title = {Ego-Body Pose Estimation via Ego-Head Pose Estimation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2023},
... | Estimating 3D human motion from an egocentric video sequence plays a critical role in human behavior understanding and has various applications in VR/AR. However, naively learning a mapping between egocentric videos and human motions is challenging, because the user's body is often unobserved by the front-facing camera... | [
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97 | SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency | [
"Yang Liu",
"Yao Zhang",
"Yixin Wang",
"Yang Zhang",
"Jiang Tian",
"Zhongchao Shi",
"Jianping Fan",
"Zhiqiang He"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Liu_SAP-DETR_Bridging_the_Gap_Between_Salient_Points_and_Queries-Based_Transformer_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Liu_SAP-DETR_Bridging_the_Gap_Between_Salient_Points_and_Queries-Based_Transformer_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Liu_SAP-DETR_Bridging_the_CVPR_2023_supplemental.pdf | 2211.02006 | title_snapshot | @InProceedings{Liu_2023_CVPR,
author = {Liu, Yang and Zhang, Yao and Wang, Yixin and Zhang, Yang and Tian, Jiang and Shi, Zhongchao and Fan, Jianping and He, Zhiqiang},
title = {SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency},
bookt... | Recently, the dominant DETR-based approaches apply central-concept spatial prior to accelerating Transformer detector convergency. These methods gradually refine the reference points to the center of target objects and imbue object queries with the updated central reference information for spatially conditional attenti... | [
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98 | GD-MAE: Generative Decoder for MAE Pre-Training on LiDAR Point Clouds | [
"Honghui Yang",
"Tong He",
"Jiaheng Liu",
"Hua Chen",
"Boxi Wu",
"Binbin Lin",
"Xiaofei He",
"Wanli Ouyang"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Yang_GD-MAE_Generative_Decoder_for_MAE_Pre-Training_on_LiDAR_Point_Clouds_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_GD-MAE_Generative_Decoder_for_MAE_Pre-Training_on_LiDAR_Point_Clouds_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Yang_GD-MAE_Generative_Decoder_CVPR_2023_supplemental.pdf | 2212.03010 | title_snapshot | @InProceedings{Yang_2023_CVPR,
author = {Yang, Honghui and He, Tong and Liu, Jiaheng and Chen, Hua and Wu, Boxi and Lin, Binbin and He, Xiaofei and Ouyang, Wanli},
title = {GD-MAE: Generative Decoder for MAE Pre-Training on LiDAR Point Clouds},
booktitle = {Proceedings of the IEEE/CVF Conference on C... | Despite the tremendous progress of Masked Autoencoders (MAE) in developing vision tasks such as image and video, exploring MAE in large-scale 3D point clouds remains challenging due to the inherent irregularity. In contrast to previous 3D MAE frameworks, which either design a complex decoder to infer masked information... | [
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99 | Towards Robust Tampered Text Detection in Document Image: New Dataset and New Solution | [
"Chenfan Qu",
"Chongyu Liu",
"Yuliang Liu",
"Xinhong Chen",
"Dezhi Peng",
"Fengjun Guo",
"Lianwen Jin"
] | https://openaccess.thecvf.com/content/CVPR2023/html/Qu_Towards_Robust_Tampered_Text_Detection_in_Document_Image_New_Dataset_CVPR_2023_paper.html | https://openaccess.thecvf.com/content/CVPR2023/papers/Qu_Towards_Robust_Tampered_Text_Detection_in_Document_Image_New_Dataset_CVPR_2023_paper.pdf | https://openaccess.thecvf.com/content/CVPR2023/supplemental/Qu_Towards_Robust_Tampered_CVPR_2023_supplemental.pdf | null | null | @InProceedings{Qu_2023_CVPR,
author = {Qu, Chenfan and Liu, Chongyu and Liu, Yuliang and Chen, Xinhong and Peng, Dezhi and Guo, Fengjun and Jin, Lianwen},
title = {Towards Robust Tampered Text Detection in Document Image: New Dataset and New Solution},
booktitle = {Proceedings of the IEEE/CVF Confere... | Recently, tampered text detection in document image has attracted increasingly attention due to its essential role on information security. However, detecting visually consistent tampered text in photographed document images is still a main challenge. In this paper, we propose a novel framework to capture more fine-gra... | [
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