2020ECCV之ReID：Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identificat
Dynamic Dual-Attentive Aggregation Learning for Visible-Infrared Person Re-Identification 简述： 现有的VI-ReID方法倾向于学习全局表示，全局表示的可辨识性有限，且对有噪信息的鲁棒性较差。针对(a)中全局信息问题和噪音问题：通过以下两个思路去解决：(b)模内加权部分聚合(IWPA)，它通过挖掘每个模内的上
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相关文章
- 1. 2019CVPR之ReID：Interaction-and-Aggregation Network for Person Re-identification
- 2. Learning Context Graph for Person Search
- 3. Camera viewpoint learning for person re-identification
- 4. 1705.IAN- The Individual Aggregation Network for Person Search 论文阅读笔记
- 5. 【Person Re-ID】Deep-Person: Learning Discriminative Deep Features for Person Re-Identification
- 6. Learning Delicate Local Representations for Multi-Person Pose Estimation
- 7. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
- 8. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 9. 《Learning Part-based Convolutional Features for Person Re-identification》TPAMI2019
- 10. View Confusion Feature Learning for Person Re-identification