The vehicle re-identification (Re-ID) has become one of most important techniques for
tracking vehicles in intelligent transport system. Vehicle Re-ID aims at matching identical …

Vehicle re-identification (Re-ID) is one of the promising applications in the field of computer
vision. Existing vehicle Re-ID methods mainly focus on global appearance features or pre …

Vehicle re-identification (Re-ID) has been attracting increasing interest in the field of
computer vision due to the growing utilization of surveillance cameras in public security …

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 …

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) is a crucial task in smart city and intelligent transportation,
aiming to match vehicle images across non-overlapping surveillance camera scenarios …

In this report, we present the Baidu-UTS submission to the AICity Challenge in CVPR 2020.
This is the winning solution to the vehicle re-identification (re-id) track. We focus on …

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-ID has recently attracted enthusiastic attention due to its potential applications in
smart city and urban surveillance. However, it suffers from large intra-class variation caused …

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