Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-id
行人重識別之cross domain Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-identification (ICCV2019) 原文鏈接 代碼鏈接 核心思想：兩個數據庫之間，圖像風格迥異。如果將圖像進行分割，那麼每一塊之間的風格差異或許會小一點。這
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相關文章
- 1. Self-similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-ID
- 2. A DIRT-T APPROACH TO UNSUPERVISED DOMAIN ADAPTATION
- 3. Domain Adaptation for Object Recognition: An Unsupervised Approach
- 4. 【ReID】EANet: Enhancing Alignment for Cross-Domain Person Re-identification
- 5. 【ReID】【Skimming】Unsupervised Cross-Dataset Transfer Learning for Person Re-identification
- 6. Asymmetric Co-Teaching for Unsupervised Cross-Domain Person Re-Identification
- 7. 《A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification》論文筆記
- 8. Maximum Classifier Discrepancy for Unsupervised Domain Adaptation
- 9. AAAI2020|Domain Adaptative Attention Learning for Unsupervised Cross-Domain Person Re-Identification
- 10. Unsupervised Domain Adaptation in the Dissimilarity Space for Person Re-identification閱讀