Cross-resolution person re-identification based on attention mechanism

被引：0
作者：
Liao H. [1 ]
Xu X. [1 ,2 ,3 ]
机构：
[1] School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan
[2] Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System, Wuhan University of Science and Technology, Wuhan
[3] Shenzhen Institute, Wuhan University, Shenzhen
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2021年 / 47卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Channel attention mechanism; Image super resolution; Person re-identification; Spatial attention mechanism; Up-sampling;
D O I：
10.13700/j.bh.1001-5965.2020.0471
中图分类号：
学科分类号：
摘要：
The resolution variation of person images poses great challenges to current person re-identification methods. To address this problem, this paper presents a cross-resolution person re-identification method. This method solves the resolution variation from two aspects. On the one hand, the spatial and channel attention mechanisms are utilized to capture person features and obtain local region; On the other hand, local information of any resolution image is recovered by the nuclear dynamic upsampling module. Comparative experiments have been conducted to verify the effectiveness of the proposed method against state-of-the-art methods on Market1501, CUHK03, and CAVIAR person re-identification datasets. The experimental results show that the proposed method has the best performance. © 2021, Editorial Board of JBUAA. All right reserved.
引用
收藏
页码：605 / 612
页数：7
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