Global Distance-distributions Separation for Unsupervised Person Re-identification

european conference on computer vision, pp. 735-751, 2020.

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Other Links: arxiv.org|academic.microsoft.com

Abstract:

Supervised person re-identification (ReID) often has poor scalability and usability in real-world deployments due to domain gaps and the lack of annotations for the target domain data. Unsupervised person ReID through domain adaptation is attractive yet challenging. Existing unsupervised ReID approaches often fail in correctly identifying...More

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