Generating Pedestrian Images for Person Re-identification

被引：0
作者：
Zhang, Zhong [1 ,2 ]
Si, Tongzhen [1 ,2 ]
Liu, Shuang [1 ,2 ]
机构：
[1] Tianjin Normal Univ, Tianjin Key Lab Wireless Mobile Commun & Power Tr, Tianjin, Peoples R China
[2] Tianjin Normal Univ, Coll Elect & Commun Engn, Tianjin, Peoples R China
来源：
COMMUNICATIONS, SIGNAL PROCESSING, AND SYSTEMS, CSPS 2018, VOL II: SIGNAL PROCESSING | 2020年 / 516卷
基金：
中国国家自然科学基金;
关键词：
Person re-identification; GAN; Generated samples;
D O I：
10.1007/978-981-13-6504-1_5
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Person re-identification (re-ID) is mainly used to search the target pedestrian in different cameras. In this paper, we employ generative adversarial network (GAN) to expand training samples and evaluate the performance of two different label assignment strategies for the generated samples. We also investigate how the number of generated samples influences the re-ID performance. We do several experiments on the Market1501 database, and the experimental results are of essential reference value to this research field.
引用
收藏
页码：37 / 43
页数：7
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