Unsupervised Person Re-identiﬁcation: Clustering and Fine-tuning阅读笔记

时间 2021-01-02

标签 reid 伪标签跨域阅读笔记繁體版

原文原文链接

Unsupervised Person Re-identiﬁcation: Clustering and Fine-tuning （PUL）阅读笔记 How? 文字解释就是：现在源域上训练一个CNN，然后到目标域对目标域图像提特征，特征喂给KMeans聚类为指定簇数(K)，对其中每簇中每个样本特征离中心样本特征的相似度(距离)，相似度大于阈值的保留，小于等于阈值的就剔除掉(噪声，最终不会被采纳，

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1. Unsupervised Person Re-identification: Clustering and Fine-tuning
2. Unsupervised Person Re-identiﬁcation: Clustering and Fine-tuning
3. Patch-based Discriminative Feature Learning for Unsupervised Person Re-identification(CVPR2019)阅读笔记
4. Cross-view Asymmetric Metric Learning for Unsupervised Person Re-identiﬁcation阅读笔记
5. Unsupervised Personalized Feature Selection--阅读笔记
6. TOMM2018_Unsupervised Person Re-identification: Clustering and Fine-tuning
7. Clustering - Unsupervised learning introduction
8. FaceNet: A Unified Embedding for Face Recognition and Clustering（论文阅读笔记）
9. CVPR 2017 Multiple People Tracking by Lifted Multicut and Person Re-identification 阅读笔记
10. 1604.Joint Detection and Identification Feature Learning for Person Search论文阅读笔记

>>更多相关文章<<