April 11, 2024, 4:44 a.m. | Yexin Liu, Weiming Zhang, Athanasios V. Vasilakos, Lin Wang

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.06683v1 Announce Type: new
Abstract: Unsupervised visible-infrared person re-identification (UVI-ReID) has recently gained great attention due to its potential for enhancing human detection in diverse environments without labeling. Previous methods utilize intra-modality clustering and cross-modality feature matching to achieve UVI-ReID. However, there exist two challenges: 1) noisy pseudo labels might be generated in the clustering process, and 2) the cross-modality feature alignment via matching the marginal distribution of visible and infrared modalities may misalign the different identities from two modalities. …

abstract alignment arxiv attention challenges clustering cs.cv detection diverse environments feature however human identification labeling labels person type unsupervised via

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