Vehicle re-identification (Re-ID) aims to retrieve images with the same vehicle ID across
different cameras. Current part-level feature learning methods typically detect vehicle parts …

Vehicle re-identification aims to identify vehicles from different cameras and has drawn
much attention in the multimedia community. In recent years, significant achievements in …

Domain generalization (DG), which doesn't require any data from target domains during
training, is more challenging but practical than unsupervised domain adaptation (UDA) …

Domain-adaptive vehicle re-identification is a challenging task that aims to transfer the
knowledge from a labeled source domain to an unlabeled target domain for effective vehicle …

The key challenge of unsupervised vehicle re-identification (Re-ID) is learning discriminative
features from unlabelled vehicle images. Numerous methods using domain adaptation have …

Fine-grained image categorization aims to distinguish the sub-categories from a certain
category of images. Generally, fine-grained data sets have the characteristics of the intra …

Reidentification (Re-id) of vehicles in a multicamera system is an essential process for traffic
control automation. Previously, there have been efforts to reidentify vehicles based on shots …