Existing vehicle re-identification methods rely on visual features to extract vehicle identity
information. However, while individual visual features enable the model to learn limited …

Abstract Vehicle Re-identification (Re-ID) has drawn extensive exploration recently;
nevertheless, the issue of accurately distinguishing features in latent space across varying …

Traffic Surveillance Systems (TSS) have become increasingly crucial in modern intelligent
transportation systems, with vision-based technologies playing a central role for scene …

The traditional view-aware based vehicle re-identification methods integrated the vehicle
view information into the training process, allowing the model parameters to learn the …

Unsupervised Domain Adaptation Vehicle Re-Identification (UDA vehicle re-ID) aims to
enable the model trained in the source domain dataset to adapt to the target domain data …

Vehicle Re-identification (Re-ID) has been broadly studied in the last decade; however, the
different camera view angles leading to confused discrimination in the feature subspace for …

As a core technology in intelligent transportation systems, vehicle re-identification has
attracted growing attention. Most existing methods use CNNs to extract global and local …