Person re-identification (Re-ID) technology plays an increasingly crucial role in intelligent
surveillance systems. Widespread occlusion significantly impacts the performance of person …

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

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

Modern data augmentation using a mixture-based technique can regularize the models from
overfitting to the training data in various computer vision applications, but a proper data …

We address the problem of visible-infrared person re-identification (VI-reID), that is,
retrieving a set of person images, captured by visible or infrared cameras, in a cross-modal …

Thanks to the recent research development in contrastive learning, the gap of visual
representation learning between supervised and unsupervised approaches has been …

As an instance-level recognition problem, person re-identification (ReID) relies on
discriminative features, which not only capture different spatial scales but also encapsulate …

Existing fully-supervised person re-identification (ReID) methods usually suffer from poor
generalization capability caused by domain gaps. The key to solving this problem lies in …