3 papers
cs.CV2026
FUSE: Frequency-domain Unification and Spectral Energy Alignment for Multi-modal Object Re-Identification
Xuanhao Qi, Tom H. Luan, Yukang Zhang +4
Despite significant progress in multi-modal Re-Identification (ReID), existing methods tend to emphasize low-frequency cues. Consequently, they focus on attributes such as color, i…
cs.CV2026
MDReID: Modality-Decoupled Learning for Any-to-Any Multi-Modal Object Re-Identification
Yingying Feng, Jie Li, Jie Hu +3
Real-world object re-identification (ReID) systems often face modality inconsistencies, where query and gallery images come from different sensors (e.g., RGB, NIR, TIR). However, m…
cs.CV2026
GSAlign: Geometric and Semantic Alignment Network for Aerial-Ground Person Re-Identification
Qiao Li, Jie Li, Yukang Zhang +3
Aerial-Ground person re-identification (AG-ReID) is an emerging yet challenging task that aims to match pedestrian images captured from drastically different viewpoints, typically…