19ICCV之REeID：RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignm
RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment 當前的問題及概述： 傳統的方法主要是通過特徵表示學習來彌補跨模態和特徵對齊之間的差異，其基本思想是通過特徵表示學習來匹配真實的RGB和IR圖像。由於兩種模式之間存在較大的交叉模態差異，因此很難在共享的特徵空間中準確地匹
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相關文章
- 1. 論文閱讀筆記之RGB-Infrared Cross-Modality Person Re-Identification via Joint Pixel and Feature Alignment
- 2. Person search: Joint Detection and Identification Feature Learning for Person Search筆記
- 3. 論文筆記之--Joint Detection and Identification Feature Learning for Person Search
- 4. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning論文筆記
- 5. 1604.Joint Detection and Identification Feature Learning for Person Search論文閱讀筆記
- 6. 論文閱讀——Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization
- 7. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 論文筆記
- 8. Joint Discriminative and Generative Learning for Person Re-identification
- 9. Joint types and operation
- 10. Spindle Net: Person Re-identification with Human Body Region Guided Feature Decomposition and Fusion