Efficient PSD Constrained Asymmetric Metric Learning for Person Re-identification(MLAPG)
1、介绍 作者提出了一种考虑半正定限制条件和采用非对称样本加权策略的逻辑度量学习算法（MLAPG），可以通过APG优化算法有效的迭代求解。 MLAPG收敛快速，并且阶数较低。作者将其应用到行人重识别问题，在四个数据集上取得了很好的效果。 2、作者的方法 1）Cross-view Logistic Metric Learning 首先是Cross-view training set的符
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相关文章
- 1. Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identification阅读笔记
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- 6. Similarity Metric Learning for Face Recognition2013
- 7. Ranked List Loss for Deep Metric Learning
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- 9. 《Efficient Deep Learning for Stereo Matching》学习笔记
- 10. Learning Mid-level Filters for Person Re-identification（CVPR2014）