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1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
時間 2020-12-30
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re-ID
行人重識別
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1505.Deep Ranking for Person Re-identification via Joint Representation Learning 這篇論文屬於深度學習領域,作者把REID看做是一個learning-to-ranking問題,作者的貢獻有: 1.特徵表達和相似性度量學習往往分開優化或者序列化的處理來進行ReID任務,且傳統方法很難有遷移和好的場景泛化能力,因此作者提出
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相關文章
1.
1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
2.
1610.Deep Learning Prototype Domains for Person Re-Identification-CUHK-SYSU-PRW 論文筆記
3.
part-aligned系列論文:1707.Deeply-Learned Part-Aligned Representations for Person Re-Identification 論文筆記
4.
1604.Joint Detection and Identification Feature Learning for Person Search論文閱讀筆記
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1705.Person Re-Identification by Deep Joint Learning of Multi-Loss Classification 論文閱讀筆記
6.
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Machine Learning & Deep Learning 論文閱讀筆記
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1604.An Enhanced Deep Feature Representation for Person Re-identification 論文筆記
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論文筆記:DEEP LEARNING FOR MONAURAL SPEECH SEPARATION
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