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EANet: Enhancing Alignment for Cross-Domain Person Re-identification
時間 2021-01-18
標籤
行人重識別(REID)
深度學習
行人重識別
cross-domain
reid
alignment
欄目
HTML
简体版
原文
原文鏈接
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
>>更多相關文章<<