Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …

Existing person re-identification methods often suffer significant performance degradation on
unseen domains, which fuels interest in domain generalizable person re-identification (DG …

In the evolving landscape of surveillance and security applications, the task of person re-
identification (re-ID) has significant importance, but also presents notable difficulties. This …

Deep learning techniques have achieved impressive progress in the task of person re-
identification. However, how to generalize a learned model from the source domain to the …

Abstract Conditional Generative Adversarial Network (cGAN) is a general purpose approach
for many image-to-image translation tasks, which aims to translate images from one form to …

Unsupervised domain adaptation (UDA) aims at adapting the model trained on a labeled
source-domain dataset to an unlabeled target-domain dataset. The task of UDA on open-set …

Unsupervised domain adaptation for person re-identification (Re-ID) suffers severe domain
discrepancies between source and target domains. To reduce the domain shift caused by …

Unsupervised person re-identification (re-ID) remains a challenging task. While extensive
research has focused on the framework design and loss function, this paper shows that …

Person search has recently been a challenging task in the computer vision domain, which
aims to search specific pedestrians from real cameras. Nevertheless, most surveillance …

Abstract Person Re-identification (P-ReID) task searches for true matches of a given query
from a large repository of non-overlapping camera's images/videos. In smart cities …