Re-ID: Person Re-identification by Local Maximal Occurrence Representation and Metric Learning 論文解析
注: 剛剛看完了這篇論文，順便整理了一下這篇論文的思路，對論文的方法表示666 項目主頁：http://www.cbsr.ia.ac.cn/users/scliao/projects/lomo_xqda/ 論文解析 行人重識別有兩個特別重要的問題： Feature representation Metric learning 在這篇論文中，作者採用的是LOMO的特徵表示方法，以及XQDA的度量學習
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相關文章
- 1. Person Re-identification by Local Maximal Occurrence Representation and Metric Learning（LOMO+XQDA）
- 2. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
- 3. 【論文筆記】Improving Person Re-identification by Attribute and Identity Learning
- 4. part-aligned系列論文：1707.ICCV.Pedestrian Alignment Network for Large-scale Person Re-identification 論文
- 5. 泛讀論文：Person-reID 行人重識別合集
- 6. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 7. 【ReID】Hierarchical and Efficient Learning for Person Re-Identification
- 8. 《Improving Person Re-identification by Attribute and Identity Learning》論文筆記
- 9. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 10. 【論文閱讀】Improving Person Re-identification by Attribute and Identity Learning