Vehicle re-identification (V-reID) has become significantly popular in the community due to
its applications and research significance. In particular, the V-reID is an important problem …

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 …

Fine-grained visual recognition is challenging because it highly relies on the modeling of
various semantic parts and fine-grained feature learning. Bilinear pooling based models …

In this paper, we tackle the vehicle Re-identification (ReID) problem which is of great
importance in urban surveillance and can be used for multiple applications. In our vehicle …

Compared to earlier multistage frameworks using CNN features, recent end-to-end deep
approaches for fine-grained recognition essentially enhance the mid-level learning …

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 …

Vehicle re-identification is an important problem and has many applications in video
surveillance and intelligent transportation. It gains increasing attention because of the recent …

Previous works on vehicle Re-ID mainly focus on extracting global features and learning
distance metrics. Because some vehicles commonly share same model and maker, it is hard …

Fine-grained image categorization is challenging due to the subtle inter-class differences.
We posit that exploiting the rich relationships between channels can help capture such …

Fine-grained visual recognition is an important problem in pattern recognition applications.
However, it is a challenging task due to the subtle interclass difference and large intraclass …