Unsupervised Group Re-identification via Adaptive Clustering-Driven Progressive Learning
Hongxu Chen,
Quan Zhang,
Jian-Huang Lai
et al.
Abstract:Group re-identification (G-ReID) aims to correctly associate groups with the same members captured by different cameras. However, supervised approaches for this task often suffer from the high cost of cross-camera sample labeling. Unsupervised methods based on clustering can avoid sample labeling, but the problem of member variations often makes clustering unstable, leading to incorrect pseudo-labels. To address these challenges, we propose an adaptive clustering-driven progressive learning approach (ACPL), wh… Show more
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