Occluded person re-identification (Re-ID) is a challenging task as persons are frequently
occluded by various obstacles or other persons, especially in the crowd scenario. To …

Occluded person re-identification (ReID) aims to match occluded person images to holistic
ones across dis-joint cameras. In this paper, we propose a novel framework by learning high …

Occluded person re-identification (ReID) aims at matching occluded person images to
holistic ones across different camera views. Target Pedestrians (TP) are often disturbed by …

RGB-Infrared (IR) person re-identification is an important and challenging task due to large
cross-modality variations between RGB and IR images. Most conventional approaches aim …

Abstract Unsupervised Domain Adaptive (UDA) person re-identification (ReID) aims at
adapting the model trained on a labeled source-domain dataset to a target-domain dataset …

When considering person re-identification (re-ID) as a retrieval process, re-ranking is a
critical step to improve its accuracy. Yet in the re-ID community, limited effort has been …

Person re-identification (Re-ID) is an important problem in video surveillance, aiming to
match pedestrian images across camera views. Currently, most works focus on RGB-based …

Person re-identification (Re-ID) is an important task in video surveillance which
automatically searches and identifies people across different cameras. Despite the …

Occluded person re-identification (re-ID) presents a challenging task due to occlusion
perturbations. Although great efforts have been made to prevent the model from being …