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Deep Association Learning for Unsupervised Video Person Re-identification
[article]
2018
arXiv
pre-print
Deep learning methods have started to dominate the research progress of video-based person re-identification (re-id). However, existing methods mostly consider supervised learning, which requires exhaustive manual efforts for labelling cross-view pairwise data. Therefore, they severely lack scalability and practicality in real-world video surveillance applications. In this work, to address the video person re-id task, we formulate a novel Deep Association Learning (DAL) scheme, the first
arXiv:1808.07301v1
fatcat:cywf42drlnhkhcfkgora7fdkha