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检索条件"任意字段=IEEE/CVF Conference on Computer Vision and Pattern Recognition"
23240 条 记 录,以下是4981-4990 订阅
排序:
Weakly Supervised Object Localization as Domain Adaption
Weakly Supervised Object Localization as Domain Adaption
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zhu, Lei She, Qi Chen, Qian You, Yunfei Wang, Boyu Lu, Yanye Peking Univ Inst Med Technol Beijing Peoples R China Bytedance AI Lab Beijing Peoples R China Peking Univ Dept Biomed Engn Beijing Peoples R China Univ Western Ontario London ON Canada Peking Univ Inst Biomed Engn Shenzhen Grad Sch Beijing Peoples R China
Weakly supervised object localization (WSOL) focuses on localizing objects only with the supervision of image-level classification masks. Most previous WSOL methods follow the classification activation map (CAM) that ... 详细信息
来源: 评论
PointGuard: Provably Robust 3D Point Cloud Classification
PointGuard: Provably Robust 3D Point Cloud Classification
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Liu, Hongbin Jia, Jinyuan Gong, Neil Zhenqiang Duke Univ Durham NC 27708 USA
3D point cloud classification has many safety-critical applications such as autonomous driving and robotic grasping. However, several studies showed that it is vulnerable to adversarial attacks. In particular, an atta... 详细信息
来源: 评论
Balanced Multimodal Learning via On-the-fly Gradient Modulation
Balanced Multimodal Learning via On-the-fly Gradient Modulat...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Peng, Xiaokang Wei, Yake Deng, Andong Wang, Dong Hu, Di Renmin Univ China Gaoling Sch Artificial Intelligence Beijing Peoples R China Beijing Key Lab Big Data Management & Anal Method Beijing Peoples R China Shanghai Jiao Tong Univ Shanghai Peoples R China Shanghai Artificial Intelligence Lab Shanghai Peoples R China
Multimodal learning helps to comprehensively understand the world, by integrating different senses. Accordingly, multiple input modalities are expected to boost model performance, but we actually find that they are no... 详细信息
来源: 评论
LSVC: A Learning-based Stereo Video Compression Framework
LSVC: A Learning-based Stereo Video Compression Framework
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Chen, Zhenghao Lu, Guo Hu, Zhihao Liu, Shan Jiang, Wei Xu, Dong Univ Sydney Sydney NSW Australia Beijing Inst Technol Beijing Peoples R China Beihang Univ Beijing Peoples R China Tencent Amer Shenzhen Peoples R China
In this work, we propose the first end-to-end optimized framework for compressing automotive stereo videos (i.e., stereo videos from autonomous driving applications) from both left and right views. Specifically, when ... 详细信息
来源: 评论
MAGVLT: Masked Generative vision-and-Language Transformer
MAGVLT: Masked Generative Vision-and-Language Transformer
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Kim, Sungwoong Jo, Daejin Lee, Donghoon Kim, Jongmin Korea Univ Dept Artificial Intelligence Seoul South Korea Kakao Brain Seongnam South Korea
While generative modeling on multimodal image-text data has been actively developed with large-scale paired datasets, there have been limited attempts to generate both image and text data by a single model rather than... 详细信息
来源: 评论
Bit-shrinking: Limiting Instantaneous Sharpness for Improving Post-training Quantization
Bit-shrinking: Limiting Instantaneous Sharpness for Improvin...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Lin, Chen Peng, Bo Li, Zheyang Tan, Wenming Ren, Ye Xiao, Jun Pu, Shiliang Hikvis Res Inst Hangzhou Peoples R China Zhe Jiang Univ Hangzhou Peoples R China
Post-training quantization (PTQ) is an effective compression method to reduce the model size and computational cost. However, quantizing a model into a low-bit one, e.g., lower than 4, is difficult and often results i... 详细信息
来源: 评论
HEAL-SWIN: A vision Transformer On The Sphere
HEAL-SWIN: A Vision Transformer On The Sphere
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Carlsson, Oscar Gerken, Jan E. Linander, Hampus Spiess, Heiner Ohlsson, Fredrik Petersson, Christoffer Persson, Daniel Univ Gothenburg Chalmers Univ Technol Dept Math Sci SE-41296 Gothenburg Sweden Tech Univ Berlin Neural Informat Proc Sci Intelligence DE-10623 Berlin Germany Umea Univ Dept Math & Math Stat Umea degrees SE-90187 Umea Sweden Zenseact SE-41756 Gothenburg Sweden
High-resolution wide-angle fisheye images are becoming more and more important for robotics applications such as autonomous driving. However, using ordinary convolutional neural networks or vision transformers on this... 详细信息
来源: 评论
Adaptive Weighted Discriminator for Training Generative Adversarial Networks
Adaptive Weighted Discriminator for Training Generative Adve...
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Zadorozhnyy, Vasily Cheng, Qiang Ye, Qiang Univ Kentucky Dept Math Lexington KY 40506 USA Univ Kentucky Inst Biomed Informat Dept Comp Sci Lexington KY 40506 USA Univ Kentucky Inst Biomed Informat Dept Internal Med Lexington KY 40506 USA
Generative adversarial network (GAN) has become one of the most important neural network models for classical unsupervised machine learning. A variety of discriminator loss functions have been developed to train GAN&#... 详细信息
来源: 评论
End-to-End Deep Kronecker-Product Matching for Person Re-identification  31
End-to-End Deep Kronecker-Product Matching for Person Re-ide...
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31st ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Shen, Yantao Xiao, Tong Li, Hongsheng Yi, Shuai Wang, Xiaogang Chinese Univ Hong Kong CUHK SenseTime Joint Lab Hong Kong Peoples R China SenseTime Res Hong Kong Peoples R China
Person re-identification aims to robustly measure similarities between person images. The significant variation of person poses and viewing angles challenges for accurate person re-identification. The spatial layout a... 详细信息
来源: 评论
Deep Deterministic Uncertainty: A New Simple Baseline
Deep Deterministic Uncertainty: A New Simple Baseline
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ieee/cvf conference on computer vision and pattern recognition (CVPR)
作者: Mukhoti, Jishnu Kirsch, Andreas van Amersfoort, Joost Torr, Philip H. S. Gal, Yarin Univ Oxford Dept Comp Sci OATML Oxford England Univ Oxford Dept Engn Sci Torr Vis Grp Oxford England
Reliable uncertainty from deterministic single-forward pass models is sought after because conventional methods of uncertainty quantification are computationally expensive. We take two complex single-forward-pass unce... 详细信息
来源: 评论