A graph structure is a powerful mathematical abstraction, which can not only represent
information about individuals but also capture the interactions between individuals for …

Real-world problems often exhibit complex relationships and dependencies, which can be
effectively captured by graph learning systems. Graph attention networks (GATs) have …

For the visible-infrared person re-identification (VIReID) task, one of the major challenges is
the modality gaps between visible (VIS) and infrared (IR) images. However, the training …

Occluded person re-identification (ReID) is a person retrieval task which aims at matching
occluded person images with holistic ones. For addressing occluded ReID, part-based …

Occluded person re-identification is a challenging task as human body parts could be
occluded by some obstacles (eg trees, cars, and pedestrians) in certain scenes. Some …

Unsupervised person re-identification (Re-ID) aims to learn discriminative features without
human-annotated labels. Recently, contrastive learning has provided a new prospect for …

In recent years, with the increasing demand for public safety and the rapid development of
intelligent surveillance networks, person re-identification (Re-ID) has become one of the hot …

Matching the daytime visible and nighttime infrared person images, namely visible infrared
person re-identification (VI-ReID), is a challenging cross-modality retrieval problem. Due to …

Person re-identification (ReID) with descriptive query (text or sketch) provides an important
supplement for general image-image paradigms, which is usually studied in a single cross …

The performance of person re-identification (re-ID) is easily affected by illumination
variations caused by different shooting times, places and cameras. Existing illumination …