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1607.CVPR-Joint Learning of Single-image and Cross-image Representations for Person ReID 论文笔记
时间 2020-12-26
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行人重识别
论文阅读笔记
ReID
深度学习
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作者将reid任务按照最终测度方法的不同,分成了两类:即按照距离loss训练方法的SIR(single-image representation)和按照对比loss训练网络的CIR(cross-image representation),作者提出了一种卷积神经网络框架,可以将两类方法整合到一个框架里,进行联合训练,最终以得分和阈值设置的形式应用训练好的模型。这样可以提升匹配率的直觉上的原因: SI
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相关文章
1.
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2020Arxiv之ReID:Deep Learning for Person Re-identification: A Survey and Outlook论文笔记
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