748 citations · 1.1k across the 20 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★ 36 cited
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…