Gait recognition is one of the most critical long-distance identification technologies and
increasingly gains popularity in both research and industry communities. Despite the …

Unsupervised person re-identification (re-ID) aims at learning discriminative representations
for person retrieval from unlabeled data. Recent techniques accomplish this task by using …

Abstract Object Re-identification (Re-ID) aims to identify specific objects across different
times and scenes, which is a widely researched task in computer vision. For a prolonged …

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 …

Person re-identification aims to retrieve persons in highly varying settings across different
cameras and scenarios, in which robust and discriminative representation learning is …

Abstract Domain generalization person re-identification (DG ReID) aims to train a model on
source domains and generalize well on unseen domains. Vision Transformer usually yields …

Abstract Domain adaptive object re-ID aims to transfer the learned knowledge from the
labeled source domain to the unlabeled target domain to tackle the open-class re …

The challenge of unsupervised person re-identification (ReID) lies in learning discriminative
features without true labels. This paper formulates unsupervised person ReID as a multi …

Unsupervised person re-identification (ReID) aims at learning discriminative identity features
without annotations. Recently, self-supervised contrastive learning has gained increasing …