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 当前的问题及概述： 传统的方法主要是通过特征表示学习来弥补跨模态和特征对齐之间的差异，其基本思想是通过特征表示学习来匹配真实的RGB和IR图像。由于两种模式之间存在较大的交叉模态差异，因此很难在共享的特征空间中准确地匹
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相关文章
- 1. 论文阅读笔记之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笔记
- 3. 论文笔记之--Joint Detection and Identification Feature Learning for Person Search
- 4. 1505.Deep Ranking for Person Re-identification via Joint Representation Learning论文笔记
- 5. 1604.Joint Detection and Identification Feature Learning for Person Search论文阅读笔记
- 6. 论文阅读——Efficient and Robust Feature Selection via Joint L2,1-Norms Minimization
- 7. 1707.Deep Learning for Person Reidentification Using Support Vector Machines 论文笔记
- 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