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 …

Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

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 …

Recently, person re-identification (Re-ID) has achieved great progress. However, current
methods largely depend on color appearance, which is not reliable when a person changes …

Long-term re-id with clothes change is a challenging problem in surveillance AI. Currently,
its major bottleneck is that this field is still missing a large realistic benchmark. In this work …

Long-Term person re-identification (LT-reID) exposes extreme challenges because of the
longer time gaps between two recording footages where a person is likely to change …

Abstract Long-Term Person Re-Identification (LT-ReID) has become increasingly crucial in
computer vision and biometrics. In this work, we aim to extend LT-ReID beyond pedestrian …

Cloth-Changing person re-identification (CC-ReID) aims at matching the same person
across different locations over a long-duration, eg, over days, and therefore inevitably has …

It is well acknowledged that person re-identification (person ReID) highly relies on visual
texture information like clothing. Despite significant progress has been made in recent years …

Person re-identification (Re-ID) plays an important role in many areas such as robotics,
multimedia and forensics. However, it becomes difficult when considering long-term …