Person re-identification (Re-ID) aims at retrieving a person of interest across multiple non-
overlapping cameras. With the advancement of deep neural networks and increasing …

In recent years, person re-identification (ReID) has received much attention since it is a
fundamental task in intelligent surveillance systems and has widespread application …

The key to address clothes-changing person re-identification (re-id) is to extract clothes-
irrelevant features, eg, face, hairstyle, body shape, and gait. Most current works mainly focus …

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

Persons are often occluded by various obstacles in person retrieval scenarios. Previous
person re-identification (re-id) methods, either overlook this issue or resolve it based on an …

Existing person re-identification (re-id) methods either assume the availability of well-
aligned person bounding box images as model input or rely on constrained attention …

Abstract Person Re-identification (ReID) is an important yet challenging task in computer
vision. Due to the diverse background clutters, variations on viewpoints and body poses, it is …

Being a cross-camera retrieval task, person re-identification suffers from image style
variations caused by different cameras. The art implicitly addresses this problem by learning …

Matching images and sentences demands a fine understanding of both modalities. In this
article, we propose a new system to discriminatively embed the image and text to a shared …

Person Re-identification (re-id) faces two major challenges: the lack of cross-view paired
training data and learning discriminative identity-sensitive and view-invariant features in the …