RoDE, a dual-model training framework with adaptive sample weighting and cluster consistency matching, improves unsupervised visible-infrared person re-identification accuracy on SYSU-MM01, RegDB, and LLCM.
Dma: Dual modality-aware alignment for visible-infrared person re-identification,
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Robust Duality Learning for Unsupervised Visible-Infrared Person Re-Identification
RoDE, a dual-model training framework with adaptive sample weighting and cluster consistency matching, improves unsupervised visible-infrared person re-identification accuracy on SYSU-MM01, RegDB, and LLCM.