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 簡述： 現有的VI-ReID方法傾向於學習全局表示，全局表示的可辨識性有限，且對有噪信息的魯棒性較差。針對(a)中全局信息問題和噪音問題：通過以下兩個思路去解決：(b)模內加權部分聚合(IWPA)，它通過挖掘每個模內的上
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相關文章
- 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 論文閱讀筆記
- 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