AI RESEARCH
Causal Bootstrapped Alignment for Unsupervised Video-Based Visible-Infrared Person Re-Identification
arXiv CS.CV
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ArXi:2604.15631v1 Announce Type: new VVI-ReID is a critical technique for all-day surveillance, where temporal information provides additional cues beyond static images. However, existing approaches rely heavily on fully supervised learning with expensive cross-modality annotations, limiting scalability. To address this issue, we investigate Unsupervised Learning for VVI-ReID (USL-VVI-ReID), which learns identity-discriminative representations directly from unlabeled video tracklets.