748 citations · 1.2k across the 24 of their papers we have counts for
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cs.CV2019★ 13 cited
Asymmetric Co-Teaching for Unsupervised Cross Domain Person Re-Identification
Fengxiang Yang, Ke Li, Zhun Zhong +7
Person re-identification (re-ID), is a challenging task due to the high variance within identity samples and imaging conditions. Although recent advances in deep learning have achi…
cs.CV2019
Learning to Adapt Invariance in Memory for Person Re-identification
Zhun Zhong, Liang Zheng, Zhiming Luo +2
This work considers the problem of unsupervised domain adaptation in person re-identification (re-ID), which aims to transfer knowledge from the source domain to the target domain.…
cs.CV2019★ 55 cited
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-identification
Zhun Zhong, Liang Zheng, Zhiming Luo +2
This paper considers the domain adaptive person re-identification (re-ID) problem: learning a re-ID model from a labeled source domain and an unlabeled target domain. Conventional…