Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

RGB-infrared person re-identification is an emerging cross-modality re-identification task,
which is very challenging due to significant modality discrepancy between RGB and infrared …

The lifelong person re-identification (LRe-ID) model retrieves a person across multiple
cameras in continuous data streams and learns new coming datasets incrementally …

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 …

Abstract Re-identification (Re-ID) is a process that seeks to identify concern individuals from
successive non-overlap** photographs. The area of computer vision has recently seen an …

Cross-modality person re-identification (ReID) aims at searching a pedestrian image of RGB
modality from infrared (IR) pedestrian images and vice versa. Recently, some approaches …

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 …

Due to the lacking of attention to the scene's essential characteristics, the existing fusion
methods suffer from the deficiency of scene distortion. In addition, the lack of groundtruth can …

Deep learning based fusion mechanisms have achieved sophisticated performance in the
field of image fusion. However, most existing approaches focus on learning global and local …

This paper focuses on RGB-infrared person re-identification, which is challenged by a large
modality gap between RGB and infrared images. Most existing methods attempt to learn …