Person Re-identification by Local Maximal Occurrence Representation and Metric Learning（LOMO+XQDA）
2015年，學術界主流都在DL，而這篇文章卻用傳統方法達到了遠超state of the art的結果： Retinex transform預處理： 爲了解決不同攝像頭下光照條件變化很大：作者在特徵提取前進行了預處理，使用的是multiscale Retinex algorithm（這個算法之前做圖像增強的時候接觸過） ，Retinex algorithm能夠增強光照陰影區域的色彩信息，有利於重識
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- 1. Re-ID: Person Re-identification by Local Maximal Occurrence Representation and Metric Learning 論文解析
- 2. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 3. Stepwise Metric Promotion for Unsupervised Video Person Re-identification
- 4. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
- 5. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 6. Improving Person Re-identification by Attribute and Identity Learning
- 7. 【論文筆記】Improving Person Re-identification by Attribute and Identity Learning
- 8. Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
- 9. 2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
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相關文章
- 1. Re-ID: Person Re-identification by Local Maximal Occurrence Representation and Metric Learning 論文解析
- 2. DIVERSITY REGULARIZED METRIC LEARNING FOR PERSON RE-IDENTIFICATION（ICIP2016）
- 3. Stepwise Metric Promotion for Unsupervised Video Person Re-identification
- 4. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
- 5. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 6. Improving Person Re-identification by Attribute and Identity Learning
- 7. 【論文筆記】Improving Person Re-identification by Attribute and Identity Learning
- 8. Re-ID: Learning Deep Feature Representation with Domain Guided Dropout for Person Re-identifiation
- 9. 2019 IET之ReID：HPILN: a feature learning framework for cross-modality person re-identification
- 10. Self-Supervised Representation Learning