Abstract Person Re-Identification (Re-ID) is a critical aspect of visual surveillance systems,
which aims to automatically recognize and locate individuals across a multi-camera network …

Person re-identification across disjoint camera views has been widely applied in video
surveillance yet it is still a challenging problem. One of the major challenges lies in the lack …

While metric learning is important for Person re-identification (RE-ID), a significant problem
in visual surveillance for cross-view pedestrian matching, existing metric models for RE-ID …

Most existing person re-identification algorithms either extract robust visual features or learn
discriminative metrics for person images. However, the underlying manifold which those …

The challenge of person re-identification (re-id) is to match individual images of the same
person captured by different nonoverlapping camera views against significant and unknown …

Person re-identification (Re-ID) aims to match identities across non-overlapping camera
views. Researchers have proposed many supervised Re-ID models which require quantities …

Person re-identification (re-id) aims to match people across non-overlapping camera views.
So far the RGB-based appearance is widely used in most existing works. However, when …

Person re-identification (REID) is an important task in video surveillance and forensics
applications. Most of previous approaches are based on a key assumption that all person …

This paper presents an end-to-end learning architecture for video-based person re-
identification by integrating convolutional neural networks (CNNs) and bidirectional …

Person re-identification is an open and challenging problem in computer vision. Existing re-
identification approaches focus on optimal methods for features matching (eg, metric …