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Unsupervised Visible-Infrared ReID via Pseudo-label Correction and Modality-level Alignment
April 11, 2024, 4:44 a.m. | Yexin Liu, Weiming Zhang, Athanasios V. Vasilakos, Lin Wang
cs.CV updates on arXiv.org arxiv.org
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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