Cross Domain Knowledge Learning with Dual-branch Adversarial Network for Vehicle Re-identification

Understand

The widespread popularization of vehicles has facilitated all people's life during the last decades.

• However, the emergence of a large number of vehicles poses the critical but challenging problem of vehicle re-identification (reID).
• Till now, for most vehicle reID algorithms, both the training and testing processes are conducted on the same annotated datasets under supervision.
• However, even a well-trained model will still cause fateful performance drop due to the severe domain bias between the trained dataset and the real-world scenes.