Asymmetric Co-Teaching for Unsupervised Cross-Domain Person Re-Identification
行人重識別之cross domain Asymmetric Co-Teaching for Unsupervised Cross-Domain Person Re-Identification (AAAI 2020) 原文鏈接 代碼連接 這篇文章爲cross domain問題提供了一個新思路:在使用聚類算法給target數據庫打僞標籤的時候，會存在一些離羣點（outliers），即這些圖像特徵不是
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相關文章
- 1. Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification閱讀筆記
- 2. AAAI2020|Asymmetric Co-Teaching for Unsupervised Cross-Domain Person Re-Identification
- 3. SYSU-MM01的多模態Re-ID數據集 異構Heterogeneous person reidentification
- 4. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 5. Stepwise Metric Promotion for Unsupervised Video Person Re-identification
- 6. 【ReID】【Skimming】Unsupervised Cross-Dataset Transfer Learning for Person Re-identification
- 7. 論文筆記 —— 《Asymmetric Tri-training for Unsupervised Domain Adaptation》
- 8. 【論文筆記】Asymmetric Tri-training for Unsupervised Domain Adaptation
- 9. 域適應方法系列1：Asymmetric Tri-training for Unsupervised Domain Adaptation
- 10. Efficient PSD Constrained Asymmetric Metric Learning for Person Re-identification(MLAPG)