Vehicle re-identification is one of the core technologies of intelligent transportation systems,
and it is crucial for the construction of smart cities. With the rapid development of deep …

This paper considers vehicle re-identification (re-ID) problem. The extreme viewpoint
variation (up to 180 degrees) poses great challenges for existing approaches. Inspired by …

In comparison with person re-identification (ReID), which has been widely studied in the
research community, vehicle ReID has received less attention. Vehicle ReID is challenging …

Vehicle Re-identification (re-id) over surveillance camera network with non-overlapping field
of view is an exciting and challenging task in intelligent transportation systems (ITS). Due to …

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 …

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 …

Existing vehicle re-identification methods commonly use spatial pooling operations to
aggregate feature maps extracted via off-the-shelf backbone networks, such as visual …

In general, vehicle images have varying resolutions due to vehicles' movements and
different camera settings. However, most existing vehicle reidentification models are single …

Vehicle Re-Identification (ReID) is of great significance for public security and intelligent
transportation. Large and comprehensive datasets are crucial for the development of vehicle …

As a significant part of Intelligent Transportation System (ITS), vehicle Re-Identification (Re-
ID) aims to retrieve all target vehicle images captured from non-overlapping cameras …