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Cross-Batch Hard Example Mining With Pseudo Large Batch for ID vs. Spot Face Recognition 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2022, 卷号: 31, 页码: 3224-3235
作者:  Tan, Zichang;  Liu, Ajian;  Wan, Jun;  Liu, Hao;  Lei, Zhen;  Guo, Guodong;  Li, Stan Z.
Adobe PDF(10124Kb)  |  收藏  |  浏览/下载：276/1  |  提交时间：2022/07/25
Face recognition  Training  Measurement  Graphics processing units  Deep learning  Logic gates  Feature extraction  Face recognition  ID vs spot  deep learning  cross-batch hard example mining  pseudo large batch  
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：340/65  |  提交时间：2020/08/31
Person re-identification  part awareness  part segmentation  multi-task learning  
Two-Level Attention Network With Multi-Grain Ranking Loss for Vehicle Re-Identification 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 9, 页码: 4328-4338
作者:  Guo, Haiyun;  Zhu, Kuan;  Tang, Ming;  Wang, Jinqiao
Adobe PDF(2562Kb)  |  收藏  |  浏览/下载：370/74  |  提交时间：2019/12/16
Two-level attention network  multi-grain ranking loss  vehicle re-identification  feature embedding  
Attention CoupleNet: Fully Convolutional Attention Coupling Network for Object Detection 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2019, 卷号: 28, 期号: 1, 页码: 113 - 126
作者:  Zhu Yousong;  Zhao Chaoyang;  Guo Haiyun;  Wang Jinqiao;  Zhao Xu;  Lu Hanqing
Adobe PDF(2526Kb)  |  收藏  |  浏览/下载：670/244  |  提交时间：2019/05/04
Object Detection  Cascade Attention  Global Structure  Local Parts  
Multi-View 3D Object Retrieval With Deep Embedding Network 期刊论文
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2016, 卷号: 25, 期号: 12, 页码: 5526-5537
作者:  Guo, Haiyun;  Wang, Jinqiao;  Gao, Yue;  Li, Jianqiang;  Lu, Hanqing
Adobe PDF(2793Kb)  |  收藏  |  浏览/下载：668/266  |  提交时间：2017/02/14
Convolutional Neural Network  Multi-view 3d Object Retrieval  Triplet Loss