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

@article{Peng2020CrossDK,
  title={Cross Domain Knowledge Learning with Dual-branch Adversarial Network for Vehicle Re-identification},
  author={Jinjia Peng and Huibing Wang and Xianping Fu},
  journal={ArXiv},
  year={2020},
  volume={abs/1905.00006}
}
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… Expand
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  • Computer Science
  • 2020 IEEE Winter Conference on Applications of Computer Vision (WACV)
  • 2020
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