1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
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
- 5. 1705.Person Re-Identification by Deep Joint Learning of Multi-Loss Classification 論文閱讀筆記
- 6. 論文筆記之--Joint Detection and Identification Feature Learning for Person Search
- 7. Machine Learning & Deep Learning 論文閱讀筆記
- 8. 1604.An Enhanced Deep Feature Representation for Person Re-identification 論文筆記
- 9. 【論文筆記】Deep Metric Learning via Facility Location
- 10. 論文筆記：DEEP LEARNING FOR MONAURAL SPEECH SEPARATION