Visible-infrared person re-identification (VI-ReID) is a challenging task due to large cross-
modality discrepancies and intra-class variations. Existing methods mainly focus on learning …

Single-modal object re-identification (ReID) faces great challenges in maintaining
robustness within complex visual scenarios. In contrast multi-modal object ReID utilizes …

Visible-infrared person re-identification (VI-ReID) is a challenging study aimed at retrieving
the same person across cameras, time, and modalities. Existing methods usually employ …

Visible–infrared person re-identification (VI-ReID) aims to retrieve images of the same
pedestrian from different modalities, where the challenges lie in the significant modality …

Vision-Language Models (VLMs), pre-trained on large-scale datasets, have shown
impressive performance in various visual recognition tasks. This advancement paves the …

Visible-Infrared person re-identification is challenging due to the large modality gap. To
bridge the gap, most studies heavily rely on the correlation of visible-infrared holistic person …

Visible-infrared person re-identification (VIReID) primarily deals with matching identities
across person images from different modalities. Due to the modality gap between visible and …

Visible–infrared person re-identification (VIPR) plays an important role in intelligent
transportation systems. Modal discrepancies between visible and infrared images seriously …

For robust multi-modal person re-identification (re-ID) models, it is crucial to effectively utilize
the complementary information and constraint relationships among different modalities …

Abstract In Re-identification (ReID) recent advancements yield noteworthy progress in both
unimodal and cross-modal retrieval tasks. However the challenge persists in develo** a …