EANet: Enhancing Alignment for Cross-Domain Person Re-identification
行人重識別之cross domain EANet: Enhancing Alignment for Cross-Domain Person Re-identification (2018arXiv) 原文鏈接 這篇文章從alignment（對準）的角度解決cross domain問題，最後的模型在source到source和source到target的效果均有了明顯的提升。本文的算法思路比較簡單清
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相關文章
- 1. 【ReID】EANet: Enhancing Alignment for Cross-Domain Person Re-identification
- 2. EANet: Enhancing Alignment for Cross-Domain Person Re-identification閱讀筆記
- 3. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 4. part-aligned系列論文：1707.ICCV.Pedestrian Alignment Network for Large-scale Person Re-identification 論文
- 5. 論文閱讀《Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification》
- 6. Deep Spatial Feature Reconstruction for Partial Person Re-identification: Alignment-free Approach筆記
- 7. [論文翻譯]Pedestrian Alignment Network for Large-scale Person Re-Identification
- 8. Pose-Guided Feature Alignment for Occluded Person Re-Identification閱讀筆記
- 9. Deep Spatial Feature Reconstruction for Partial Person Re-identification Alignment-Free Approach(nt)
- 10. Deeply-Learned Spatial Alignment for Person Re-Identification 論文閱讀記錄