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1604.Joint Detection and Identification Feature Learning for Person Search论文阅读笔记
时间 2020-12-29
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深度学习
行人重识别
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前言: Li et al. 和Ahmed et al. 提出方法:一对裁剪图像输入+binary verification loss 训练参数 Ding et al. 和Cheng et al. 提出方法:三图像输入(triplet sample)+binary triplet loss 训练参数,minimize the feature distance between the same per
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相关文章
1.
论文笔记之--Joint Detection and Identification Feature Learning for Person Search
2.
Person search: Joint Detection and Identification Feature Learning for Person Search笔记
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【论文阅读】Batch Feature Erasing for Person Re-identification and Beyond
9.
1705.Person Re-Identification by Deep Joint Learning of Multi-Loss Classification 论文阅读笔记
10.
【论文阅读】 Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification
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