Discriminative Feature Learning With Foreground Attention for Person Re-Identification

IEEE Transactions on Image Processing(2019)

引用 61|浏览0
暂无评分
摘要
The performance of person re-identification (Re-ID) has been seriously affected by the large cross-view appearance variations caused by mutual occlusions and background clutter. Hence, learning a feature representation that can adaptively emphasize the foreground persons becomes very critical to solve the person Re-ID problem. In this paper, we propose a simple yet effective foreground attentive n...
更多
查看译文
关键词
Feature extraction,Measurement,Neural networks,Learning systems,Decoding,Training,Task analysis
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要