Part feature learning is critical for fine-grained semantic understanding in vehicle re-
identification. However, existing approaches directly model part features and global …

This paper aims to learn a domain-generalizable (DG) person re-identification (ReID)
representation from large-scale videos without any annotation. Prior DG ReID methods …

The explosive increase in vision transformers studies has shown remarkable progress in
vision tasks such as image classification and detection. However, in instance-level image …

Person re-identification (re-ID) aims to match the same person across different cameras.
However, most existing re-ID methods assume that people wear the same clothes in …

Unsupervised domain adaptation (UDA) in person re-identification (re-ID) is a challenging
task, aiming to learn a model with labeled source data and unlabeled target data to …

Unsupervised domain adaptation (UDA) techniques for person re-identification (ReID) have
been extensively studied to facilitate the transfer of knowledge from labeled source domains …

Occluded person re-identification (ReID) is a challenging task due to more background
noises and incomplete foreground information. Although existing human parsing-based …

The existing unsupervised domain adaptation (UDA) methods on person re-identification (re-
ID) often employ clustering to assign pseudo labels for unlabeled target domain samples …

As a challenging task, unsupervised person ReID aims to match the same identity with query
images which does not require any labeled information. In general, most existing …

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