Person re-identification (re-id) remains challenging due to significant intra-class variations
across different cameras. Recently, there has been a growing interest in using generative …

In this paper, we introduce Random Erasing, a new data augmentation method for training
the convolutional neural network (CNN). In training, Random Erasing randomly selects a …

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 …

Person re-identification is a challenging task mainly due to factors such as background
clutter, pose, illumination and camera point of view variations. These elements hinder the …

In the past few years, the field of computer vision has gone through a revolution fueled
mainly by the advent of large datasets and the adoption of deep convolutional neural …

Key to effective person re-identification (Re-ID) is modelling discriminative and view-
invariant factors of person appearance at both high and low semantic levels. Recently …

Person re-identification is a challenging retrieval task that requires matching a person's
acquired image across non-overlapping camera views. In this paper we propose an effective …

Person re-identification (ReID) is an important task in the field of intelligent security. A key
challenge is how to capture human pose variations, while existing benchmarks (ie …

Metric learning aims to construct an embedding where two extracted features corresponding
to the same identity are likely to be closer than features from different identities. This paper …

Person re-identification (re-ID) is mostly viewed as an image retrieval problem. This task
aims to search a query person in a large image pool. In practice, person re-ID usually adopts …