Visible Infrared Person Re Identification

Visible-infrared person re-identification (VI-ReID) focuses on matching individuals across images captured by visible and infrared cameras, a crucial task for robust surveillance systems. Current research emphasizes bridging the significant modality gap between these image types through various techniques, including transformer networks, contrastive learning, and optimal transport, often incorporating multi-feature generation, attention mechanisms, and prototype learning to improve accuracy. These advancements aim to create more robust and reliable person identification systems, particularly in challenging lighting conditions or scenarios with limited visibility, impacting fields like security, forensics, and human-computer interaction.