Transformers are more and more popular in computer vision, which treat an image as a
sequence of patches and learn robust global features from the sequence. However, pure …

The widespread use of surveillance cameras toward smart and safe cities poses the critical
but challenging problem of vehicle reidentification (Re-ID). The state-of-the-art research …

Vehicle re-identification (re-ID) has the huge potential to contribute to the intelligent video
surveillance. However, it suffers from challenges that different vehicle identities with a similar …

In order to resist the adverse effect of viewpoint variations, we design quadruple directional
deep learning networks to extract quadruple directional deep learning features (QD-DLF) of …

Vehicle re-identification (re-ID) is to identify the same vehicle across different cameras. It'sa
significant but challenging topic, which has received little attention due to the complex intra …

Vehicle re-identification (re-ID) is an area that has received far less attention in the computer
vision community than the prevalent person re-ID. Possible reasons for this slow progress …

Vehicle re-identification is an important problem and becomes desirable with the rapid
expansion of applications in video surveillance and intelligent transportation. By recalling …

Vehicle Re-Identification (Re-ID) is challenging because vehicles of the same model
commonly show similar appearance. We tackle this challenge by proposing a Global …

In this paper we tackle the problem of vehicle re-identification in a camera network utilizing
triplet embeddings. Re-identification is the problem of matching appearances of objects …

Vehicle re-identification (re-ID) aims to retrieve the image of the same vehicles across
multiple cameras. It has attracted wide attention in the field of computer vision owing to the …