Open access
Aug 2026
Dynamic Uncertainty Learning with Noisy Correspondence for Text-based Person Retrieval
Dynamic Uncertainty with Noisy Correspondences (DUNC), a novel framework that incorporates two key components that incorporates Cross-modal Evidential Learning (CEL), which models bidirectional alignment uncertainty using a Dirichlet distribution to capture the confidence in image–text similarity, and Dynamic Robust Lo...
Ze-Qun Xie, Chu-Xin Wang, Si-Hang Cai et al.
· ACM Transactions on Informat... · 0 citations