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检索条件"任意字段=1994 IEEE Computer-Society Conference on Computer Vision and Pattern Recognition"
22906 条 记 录,以下是4731-4740 订阅
排序:
Predicting Goal-directed Human Attention Using Inverse Reinforcement Learning
Predicting Goal-directed Human Attention Using Inverse Reinf...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Yang, Zhibo Huang, Lihan Chen, Yupei Wei, Zijun Ahn, Seoyoung Zelinsky, Gregory Samaras, Dimitris Hoai, Minh SUNY Stony Brook Stony Brook NY 11794 USA Adobe Inc San Jose CA USA
Human gaze behavior prediction is important for behavioral vision and for computer vision applications. Most models mainly focus on predicting free-viewing behavior using saliency maps, but do not generalize to goal-d... 详细信息
来源: 评论
NVTC: Nonlinear Vector Transform Coding
NVTC: Nonlinear Vector Transform Coding
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Feng, Runsen Guo, Zongyu Li, Weiping Chen, Zhibo Univ Sci & Technol China Hefei Peoples R China
In theory, vector quantization (VQ) is always better than scalar quantization (SQ) in terms of rate-distortion (RD) performance [33]. Recent state-of-the-art methods for neural image compression are mainly based on no... 详细信息
来源: 评论
Data-driven Feature Tracking for Event Cameras
Data-driven Feature Tracking for Event Cameras
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Messikommer, Nico Fang, Carter Gehrig, Mathias Scaramuzza, Davide Univ Zurich Robot & Percept Grp Zurich Switzerland
Because of their high temporal resolution, increased resilience to motion blur, and very sparse output, event cameras have been shown to be ideal for low-latency and low-bandwidth feature tracking, even in challenging... 详细信息
来源: 评论
Contrast Prior and Fluid Pyramid Integration for RGBD Salient Object Detection  32
Contrast Prior and Fluid Pyramid Integration for RGBD Salien...
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32nd ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhao, Jia-Xing Cao, Yang Fan, Deng-Ping Cheng, Ming-Ming Li, Xuan-Yi Zhang, Le Nankai Univ CS TKLNDST Tianjin Peoples R China ASTAR Singapore Singapore
The large availability of depth sensors provides valuable complementary information for salient object detection (SOD) in RGBD images. However, due to the inherent difference between RGB and depth information, extract... 详细信息
来源: 评论
Cross-view and Cross-pose Completion for 3D Human Understanding
Cross-view and Cross-pose Completion for 3D Human Understand...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Armando, Matthieu Galaaoui, Salma Baradel, Fabien Lucas, Thomas Leroy, Vincent Bregier, Romain Weinzaepfel, Philippe Rogez, Gregory NAVER LABS Europe Meylan France
Human perception and understanding is a major domain of computer vision which, like many other vision subdomains recently, stands to gain from the use of large models pre-trained on large datasets. We hypothesize that... 详细信息
来源: 评论
Natural and Realistic Single Image Super-Resolution with Explicit Natural Manifold Discrimination  32
Natural and Realistic Single Image Super-Resolution with Exp...
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32nd ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Soh, Jae Woong Park, Gu Yong Jo, Junho Cho, Nam Ik Seoul Natl Univ Dept ECE INMC Seoul South Korea
Recently, many convolutional neural networksfor single image super-resolution (SISR) have been proposed, which focus on reconstructingthe high-resolutionimages in terms of objective distortion measures. However, the n... 详细信息
来源: 评论
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction  32
Multi-Agent Tensor Fusion for Contextual Trajectory Predicti...
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32nd ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhao, Tianyang Xu, Yifei Monfort, Mathew Choi, Wongun Baker, Chris Zhao, Yibiao Wang, Yizhou Wu, Ying Nian ISEE AI Cambridge MA USA Peking Univ Beijing Peoples R China Univ Calif Los Angeles Los Angeles CA 90024 USA MIT CSAIL Cambridge MA USA
Accurate prediction of others' trajectories is essential for autonomous driving. Trajectory prediction is challenging because it requires reasoning about agents' past movements, social interactions among varyi... 详细信息
来源: 评论
Collaborative and Adversarial Network for Unsupervised domain adaptation  31
Collaborative and Adversarial Network for Unsupervised domai...
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31st ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Zhang, Weichen Ouyang, Wanli Li, Wen Xu, Dong Univ Sydney Sch Elect & Informat Engn Sydney NSW Australia Swiss Fed Inst Technol Comp Vis Lab Zurich Switzerland
In this paper, we propose a new unsupervised domain adaptation approach called Collaborative and Adversarial Network (CAN) through domain-collaborative and domain adversarial training of neural networks. We add severa... 详细信息
来源: 评论
Background-Aware Pooling and Noise-Aware Loss for Weakly-Supervised Semantic Segmentation
Background-Aware Pooling and Noise-Aware Loss for Weakly-Sup...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Oh, Youngmin Kim, Beomjun Ham, Bumsub Yonsei Univ Sch Elect & Elect Engn Seoul South Korea
We address the problem of weakly-supervised semantic segmentation (WSSS) using bounding box annotations. Although object bounding boxes are good indicators to segment corresponding objects, they do not specify object ... 详细信息
来源: 评论
Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification
Joint Distribution Matters: Deep Brownian Distance Covarianc...
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ieee/CVF conference on computer vision and pattern recognition (CVPR)
作者: Xie, Jiangtao Long, Fei Lv, Jiaming Wang, Qilong Li, Peihua Dalian Univ Technol Dalian Peoples R China Tianjin Univ Tianjin Peoples R China
Few-shot classification is a challenging problem as only very few training examples are given for each new task. One of the effective research lines to address this challenge focuses on learning deep representations d... 详细信息
来源: 评论