Transferable Joint Attribute-Identity Deep Learning for Unsupervised Person Re-Identification

CVPR 2018 Jingya WangXiatian ZhuShaogang GongWei Li

Most existing person re-identification (re-id) methods require supervised model learning from a separate large set of pairwise labelled training data for every single camera pair. This significantly limits their scalability and usability in real-world large scale deployments with the need for performing re-id across many camera views... (read more)

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