Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation

时间 2020-12-29

标签 Re-id 行人再识别论文解析 DGD Deep-Model 栏目 HTML 繁體版

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刚刚看完这篇论文，整理了一下思路。这篇论文基于神经元在学习不同特征时活跃程度不同而提出DGD的方法，也是666的论文：https://arxiv.org/abs/1604.07528 代码：https://github.com/Cysu/dgd_person_reid 论文解析文章一开始，作者解释了为什么要使用多个数据集进行训练： Learning generic and robust fea

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1. 1604. Learning deep feature representations with domain guided dropout for re-id论文阅读笔记
2. 1604.An Enhanced Deep Feature Representation for Person Re-identification 论文笔记
3. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning论文笔记
4. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
5. 【ReID】EANet: Enhancing Alignment for Cross-Domain Person Re-identification
6. part-aligned系列论文：1707.Deep Representation Learning with Part Loss for Person ReID 论文阅读笔记
7. 【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
8. View Confusion Feature Learning for Person Re-identification
9. 2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
10. Instance-Guided Context Rendering for Cross-Domain Person Re-Identification
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1. 1604. Learning deep feature representations with domain guided dropout for re-id论文阅读笔记
2. 1604.An Enhanced Deep Feature Representation for Person Re-identification 论文笔记
3. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning论文笔记
4. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
5. 【ReID】EANet: Enhancing Alignment for Cross-Domain Person Re-identification
6. part-aligned系列论文：1707.Deep Representation Learning with Part Loss for Person ReID 论文阅读笔记
7. 【ReID】Learning Discriminative Features with Multiple Granularities for Person Re-identification
8. View Confusion Feature Learning for Person Re-identification
9. 2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
10. Instance-Guided Context Rendering for Cross-Domain Person Re-Identification

>>更多相关文章<<