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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2000"
19489 条 记 录,以下是4761-4770 订阅
排序:
MotionRNN: A Flexible Model for Video Prediction with Spacetime-Varying Motions
MotionRNN: A Flexible Model for Video Prediction with Spacet...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wu, Haixu Yao, Zhiyu Wang, Jianmin Long, Mingsheng Tsinghua Univ Sch Software BNRist Beijing Peoples R China
This paper tackles video prediction from a new dimension of predicting spacetime-varying motions that are incessantly changing across both space and time. Prior methods mainly capture the temporal state transitions bu... 详细信息
来源: 评论
Automatic Play Segmentation of Hockey Videos
Automatic Play Segmentation of Hockey Videos
收藏 引用
ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Pidaparthy, Hemanth Dowling, Michael H. Elder, James H. York Univ N York ON Canada Queens Univ Kingston ON Canada
Most team sports such as hockey involve periods of active play interleaved with breaks in play. When watching a game remotely, many fans would prefer an abbreviated game showing only periods of active play. Here we ad... 详细信息
来源: 评论
Adversarial Robustness under Long-Tailed Distribution
Adversarial Robustness under Long-Tailed Distribution
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wu, Tong Liu, Ziwei Huang, Qingqiu Wang, Yu Lin, Dahua Chinese Univ Hong Kong Hong Kong Peoples R China Nanyang Technol Univ S Lab Singapore Singapore Huawei Shenzhen Peoples R China Tsinghua Univ Beijing Peoples R China SenseTime CUHK Joint Lab Hong Kong Peoples R China Ctr Perceptual & Interact Intelligence Hong Kong Peoples R China
Adversarial robustness has attracted extensive studies recently by revealing the vulnerability and intrinsic characteristics of deep networks. However;existing works on adversarial robustness mainly focus on balanced ... 详细信息
来源: 评论
Activity-Biometrics: Person Identification from Daily Activities
Activity-Biometrics: Person Identification from Daily Activi...
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conference on computer vision and pattern recognition (cvpr)
作者: Shehreen Azad Yogesh Singh Rawat Center for Research in Computer Vision University of Central Florida
In this work, we study a novel problem which focuses on person identification while performing daily activities. Learning biometric features from RGB videos is challenging due to spatio-temporal complexity and presenc... 详细信息
来源: 评论
ARVo: Learning All-Range Volumetric Correspondence for Video Deblurring
ARVo: Learning All-Range Volumetric Correspondence for Video...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Li, Dongxu Xu, Chenchen Zhang, Kaihao Yu, Xin Zhong, Yiran Ren, Wenqi Suominen, Hanna Li, Hongdong Australian Natl Univ Canberra ACT Australia DATA61 CSIRO Sydney NSW Australia UTS Sydney NSW Australia Chinese Acad Sci IIE Beijing Peoples R China Univ Turku Turku Finland
Video deblurring models exploit consecutive frames to remove blurs from camera shakes and object motions. In order to utilize neighboring sharp patches, typical methods rely mainly on homography or optical flows to sp... 详细信息
来源: 评论
Not just Compete, but Collaborate: Local Image-to-Image Translation via Cooperative Mask Prediction
Not just Compete, but Collaborate: Local Image-to-Image Tran...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Kim, Daejin Khan, Mohammad Azam Choo, Jaegul Korea Adv Inst Sci & Technol Daejeon South Korea Dhaka Power Distribut Co Ltd Dhaka Bangladesh
Facial attribute editing aims to manipulate the image with the desired attribute while preserving the other details. Recently, generative adversarial networks along with the encoder-decoder architecture have been util... 详细信息
来源: 评论
Non-Salient Region Object Mining for Weakly Supervised Semantic Segmentation
Non-Salient Region Object Mining for Weakly Supervised Seman...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Yao, Yazhou Chen, Tao Xie, Guo-Sen Zhang, Chuanyi Shen, Fumin Wu, Qi Tang, Zhenmin Zhang, Jian Nanjing Univ Sci & Technol Nanjing Peoples R China Mohamed bin Zayed Univ AI Abu Dhabi U Arab Emirates Univ Elect Sci & Technol China Chengdu Peoples R China Univ Adelaide Adelaide SA Australia Univ Technol Sydney Sydney NSW Australia
Semantic segmentation aims to classify every pixel of an input image. Considering the difficulty of acquiring dense labels, researchers have recently been resorting to weak labels to alleviate the annotation burden of... 详细信息
来源: 评论
SCF-Net: Learning Spatial Contextual Features for Large-Scale Point Cloud Segmentation
SCF-Net: Learning Spatial Contextual Features for Large-Scal...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Fan, Siqi Dong, Qiulei Zhu, Fenghua Lv, Yisheng Ye, Peijun Wang, Fei-Yue CASIA State Key Lab Management & Control Complex Syst Beijing Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China CASIA Natl Lab Pattern Recognit Beijing Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Beijing Peoples R China
How to learn effective features from large-scale point clouds for semantic segmentation has attracted increasing attention in recent years. Addressing this problem, we propose a learnable module that learns Spatial Co... 详细信息
来源: 评论
Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Image Retrieval
Sketch-QNet: A Quadruplet ConvNet for Color Sketch-based Ima...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Fuentes, Anibal Saavedra, Jose M. Impresee Inc 600 Calif St San Francisco CA 94108 USA
Architectures based on siamese networks with triplet loss have shown outstanding performance on the image-based similarity search problem. This approach attempts to discriminate between positive (relevant) and negativ... 详细信息
来源: 评论
ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning
ORDisCo: Effective and Efficient Usage of Incremental Unlabe...
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ieee/CVF conference on computer vision and pattern recognition (cvpr)
作者: Wang, Liyuan Yang, Kuo Li, Chongxuan Hong, Lanqing Li, Zhenguo Zhu, Jun Tsinghua Univ BNRist Ctr Inst AI Dept Comp Sci & TechTHBI Lab Beijing Peoples R China Huawei Noahs Ark Lab Shenzhen Peoples R China
Continual learning usually assumes the incoming data are fully labeled, which might not be applicable in real applications. In this work, we consider semi-supervised continual learning (SSCL) that incrementally learns... 详细信息
来源: 评论