Gait recognition is an appealing biometric modality which aims to identify individuals based
on the way they walk. Deep learning has reshaped the research landscape in this area …

Gait recognition aims to identify a person at a distance, serving as a promising solution for
long-distance and less-cooperation pedestrian recognition. Recently, significant advances …

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

Entangled representation of clothing and identity (ID)-intrinsic clues are potentially
concomitant in conventional person Re-IDentification (ReID). Nevertheless, eliminating the …

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 …

Gait recognition, applied to identify individual walking patterns in a long-distance, is one of
the most promising video-based biometric technologies. At present, most gait recognition …

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 …

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 …