Unsupervised Person Re-identification: Clustering and Fine-tuning
1、介绍 基于全监督的行人重识别问题取得了很大的进展。但是基于无监督的行人重识别问题的进展则相对缓慢。现有研究主要集中在人工提取特征然后使用无监督方法分类上，针对的数据集规模也比较小。作者提出了一个PUL(PROGRESSIVE UNSUPERVISED LEARNING)的方法，率先把深度学习框架应用到大规模数据集无监督行人重识别问题上。 2、作者的方法 作者将他的方法命名为PUL(PROGRE
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相关文章
- 1. Unsupervised Person Re-identification: Clustering and Fine-tuning
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- 10. Stepwise Metric Promotion for Unsupervised Video Person Re-identification