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Visible-Infrared Person Re-Identification via Patch-Mixed Cross-Modality Learning
May 1, 2024, 4:46 a.m. | Zhihao Qian, Yutian Lin, Bo Du
cs.CV updates on arXiv.org arxiv.org
Abstract: Visible-infrared person re-identification (VI-ReID) aims to retrieve images of the same pedestrian from different modalities, where the challenges lie in the significant modality discrepancy. To alleviate the modality gap, recent methods generate intermediate images by GANs, grayscaling, or mixup strategies. However, these methods could introduce extra data distribution, and the semantic correspondence between the two modalities is not well learned. In this paper, we propose a Patch-Mixed Cross-Modality framework (PMCM), where two images of the …
abstract arxiv challenges cs.cv data distribution extra gans gap generate however identification images intermediate mixed pedestrian person strategies type via
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