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Exploring Intrinsic Discrimination and Consistency for Weakly Supervised Object Localization 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2024, 卷号: 33, 期号: 0, 页码: 1045 - 1058
作者:  Changwei Wang;  Rongtao Xu;  Shibiao Xu;  Weiliang Meng;  Ruisheng Wang;  Xiaopeng Zhang
Adobe PDF(3269Kb)  |  收藏  |  浏览/下载：4/1  |  提交时间：2024/05/29
Weakly supervised object localization  intrinsic discrimination and consistency  deep metric learning  geometric transformation consistency  
Narrowing the Gap: Improved Detector Training With Noisy Location Annotations 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 6369-6380
作者:  Wang, Shaoru;  Gao, Jin;  Li, Bing;  Hu, Weiming
Adobe PDF(1489Kb)  |  收藏  |  浏览/下载：221/26  |  提交时间：2022/11/14
Annotations  Noise measurement  Detectors  Task analysis  Training  Object detection  Degradation  Object detection  noisy label  Bayesian estimation  teacher-student learning  
Nocal-Siam: Refining Visual Features and Response With Advanced Non-Local Blocks for Real-Time Siamese Tracking 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2021, 卷号: 30, 页码: 2656-2668
作者:  Tan, Huibin;  Zhang, Xiang;  Zhang, Zhipeng;  Lan, Long;  Zhang, Wenju;  Luo, Zhigang
Adobe PDF(2898Kb)  |  收藏  |  浏览/下载：174/41  |  提交时间：2021/03/29
Target tracking  Visualization  Feature extraction  Real-time systems  Oceans  Convolution  Task analysis  Siamese trackers  non-local attention  supervisedly attentive  
Domain Adaptation by Class Centroid Matching and Local Manifold Self-Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 9703-9718
作者:  Tian, Lei;  Tang, Yongqiang;  Hu, Liangchen;  Ren, Zhida;  Zhang, Wensheng
Adobe PDF(3443Kb)  |  收藏  |  浏览/下载：344/72  |  提交时间：2021/01/06
Domain adaptation  class centroid matching  local manifold self-learning  
Skeleton-Based Action Recognition With Multi-Stream Adaptive Graph Convolutional Networks 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 期号: 29, 页码: 9532-9545
作者:  Shi, Lei;  Zhang, Yifan;  Cheng, Jian;  Lu, Hanqing
Adobe PDF(2849Kb)  |  收藏  |  浏览/下载：380/148  |  提交时间：2020/11/05
Skeleton-based action recognition, graph convolutional network, adaptive graph, multi-stream network.  
Attention-Based Pedestrian Attribute Analysis 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 12, 页码: 6126-6140
作者:  Zichang Tan;  Yang Yang;  Jun Wan;  Hanyuan Hang;  Guodong Guo;  Stan Z. Li
Adobe PDF(3457Kb)  |  收藏  |  浏览/下载：221/41  |  提交时间：2020/10/27
Pedestrian attribute analysis  attention mechanism  pedestrian parsing  
Improve Person Re-Identification With Part Awareness Learning 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 页码: 7468-7481
作者:  Huang, Houjing;  Yang, Wenjie;  Lin, Jinbin;  Huang, Guan;  Xu, Jiamiao;  Wang, Guoli;  Chen, Xiaotang;  Huang, Kaiqi
Adobe PDF(3927Kb)  |  收藏  |  浏览/下载：318/56  |  提交时间：2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning  
Tangent Fisher Vector on Matrix Manifolds for Action Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 1, 页码: 3052-3064
作者:  Luo, Guan;  Wei, Jiutong;  Hu, Weiming;  Maybank, Stephen J.
浏览  |  Adobe PDF(2396Kb)  |  收藏  |  浏览/下载：360/78  |  提交时间：2020/04/07
Manifolds  Video sequences  Observability  Videos  Covariance matrices  Kernel  Computational modeling  Action recognition  Fisher vector  Grassmann manifold  Hankel matrix  matrix manifold  
Tensor Multi-Task Learning for Person Re-Identification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2020, 卷号: 29, 期号: 1, 页码: 2463-2477
作者:  Zhang, Zhizhong;  Xie, Yuan;  Zhang, Wensheng;  Tang, Yongqiang;  Tian, Qi
Adobe PDF(1444Kb)  |  收藏  |  浏览/下载：351/59  |  提交时间：2020/03/30
Cameras  Task analysis  Measurement  Visualization  Training  Computational modeling  Person re-identification  multi-task learning  tensor optimization  
SMART: Joint Sampling and Regression for Visual Tracking 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 8, 页码: 3923-3935
作者:  Gao, Junyu;  Zhang, Tianzhu;  Xu, Changsheng
Adobe PDF(9244Kb)  |  收藏  |  浏览/下载：340/42  |  提交时间：2019/09/30
Visual tracking  deep learning  sampling and regression