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检索条件"任意字段=Conference on Computer Vision and Pattern Recognition"
30983 条 记 录,以下是4771-4780 订阅
排序:
On Learning Contrastive Representations for Learning with Noisy Labels
On Learning Contrastive Representations for Learning with No...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yi, Li Liu, Sheng She, Qi McLeod, A. Ian Wang, Boyu Univ Western Ontario London ON Canada NYU Ctr Data Sci New York NY 10003 USA ByteDance Inc Beijing Peoples R China Vector Inst Toronto ON Canada
Deep neural networks are able to memorize noisy labels easily with a softmax cross entropy (CE) loss. Previous studies attempted to address this issue focus on incorporating a noise-robust loss function to the CE loss... 详细信息
来源: 评论
EVSRNet: Efficient Video Super-Resolution with Neural Architecture Search
EVSRNet: Efficient Video Super-Resolution with Neural Archit...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Liu, Shaoli Zheng, Chengjian Lu, Kaidi Gao, Si Wang, Ning Wang, Bofei Zhang, Diankai Zhang, Xiaofeng Xu, Tianyu ZTE Corp State Key Lab Mobile Network & Mobile Multimedia Shenzhen Peoples R China
With the development of convolutional neural networks (CNN), the super-resolution results of CNN-based method have far surpassed traditional method. In particular, the CNN-based single image super-resolution method ha... 详细信息
来源: 评论
Object-aware Video-language Pre-training for Retrieval
Object-aware Video-language Pre-training for Retrieval
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Wang, Alex Jinpeng Ge, Yixiao Cai, Guanyu Yan, Rui Lin, Xudong Shan, Ying Qie, Xiaohu Shou, Mike Zheng Natl Univ Singapore Show Lab Singapore Singapore ARC Lab Beijing Peoples R China Tencent PCG Beijing Peoples R China Columbia Univ New York NY 10027 USA Tongji Univ Shanghai Peoples R China
Recently, by introducing large-scale dataset and strong transformer network, video-language pre-training has shown great success especially for retrieval. Yet, existing video-language transformer models do not explici... 详细信息
来源: 评论
Imposing Consistency for Optical Flow Estimation
Imposing Consistency for Optical Flow Estimation
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Jeong, Jisoo Lin, Jamie Menjay Porikli, Fatih Kwak, Nojun Qualcomm AI Res San Diego CA 92121 USA Google Res Mountain View CA USA Seoul Natl Univ Seoul South Korea
Imposing consistency through proxy tasks has been shown to enhance data-driven learning and enable self-supervision in various tasks. This paper introduces novel and effective consistency strategies for optical flow e... 详细信息
来源: 评论
Transferable Query Selection for Active Domain Adaptation
Transferable Query Selection for Active Domain Adaptation
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Fu, Bo Cao, Zhangjie Wang, Jianmin Long, Mingsheng Tsinghua Univ Sch Software BNRist Beijing Peoples R China
Unsupervised domain adaptation (UDA) enables transferring knowledge from a related source domain to a fully unlabeled target domain. Despite the significant advances in UDA, the performance gap remains quite large bet... 详细信息
来源: 评论
Multi stain graph fusion for multimodal integration in pathology
Multi stain graph fusion for multimodal integration in patho...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Dwivedi, Chaitanya Nofallah, Shima Pouryahya, Maryam Iyer, Janani Leidal, Kenneth Chung, Chuhan Watkins, Timothy Billin, Andrew Myers, Robert Abel, John Behrooz, Ali PathAI Inc Boston MA 02215 USA Gilead Sci Inc Foster City CA 94404 USA
In pathology, tissue samples are assessed using multiple staining techniques to enhance contrast in unique histologic features. In this paper, we introduce a multimodal CNN-GNN based graph fusion approach that leverag... 详细信息
来源: 评论
Multi-class Token Transformer for Weakly Supervised Semantic Segmentation
Multi-class Token Transformer for Weakly Supervised Semantic...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xu, Lian Ouyang, Wanli Bennamoun, Mohammed Boussaid, Farid Xu, Dan Univ Western Australia Nedlands WA Australia Univ Sydney SenseTime Comp Vis Grp Sydney NSW Australia Hong Kong Univ Sci & Technol Hong Kong Peoples R China
This paper proposes a new transformer-based framework to learn class-specific object localization maps as pseudo labels for weakly supervised semantic segmentation (WSSS). Inspired by the fact that the attended region... 详细信息
来源: 评论
Compatibility-aware Heterogeneous Visual Search
Compatibility-aware Heterogeneous Visual Search
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Duggal, Rahul Zhou, Hao Yang, Shuo Xiong, Yuanjun Xia, Wei Tu, Zhuowen Soatto, Stefano Amazon AI AWS Seattle WA 98121 USA Georgia Inst Technol Atlanta GA 30332 USA Amazon AI Seattle WA USA
We tackle the problem of visual search under resource constraints. Existing systems use the same embedding model to compute representations (embeddings) for the query and gallery images. Such systems inherently face a... 详细信息
来源: 评论
Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation
Overcoming Catastrophic Forgetting in Incremental Object Det...
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Feng, Tao Wang, Mang Yuan, Hangjie Alibaba Grp Hangzhou Peoples R China Zhejiang Univ Hangzhou Peoples R China
Traditional object detectors are ill-equipped for incremental learning. However, fine-tuning directly on a well-trained detection model with only new data will lead to catastrophic forgetting. Knowledge distillation i... 详细信息
来源: 评论
VMCML: Video and Music Matching via Cross-Modality Lifting
VMCML: Video and Music Matching via Cross-Modality Lifting
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IEEE/CVF conference on computer vision and pattern recognition (CVPR)
作者: Lee, Yi-Shan Tseng, Wei-Cheng Wang, Fu-En Sun, Min Natl Tsing Hua Univ Hsinchu Taiwan Univ Toronto Toronto ON Canada Vector Inst Toronto ON Canada
We propose a content-based system for matching video and background music. The system aims to address the challenges in music recommendation for new users or new music give short-form videos. To this end, we propose a... 详细信息
来源: 评论