PFNet: Part-guided feature-combination network for vehicle re-identification

Author:

Qian Jiahe,Zhao JiandongORCID

Publisher

Springer Science and Business Media LLC

Reference49 articles.

1. Liu X, Liu W, Mei T et al (2017) Provid: progressive and multimodal vehicle reidentification for large-scale urban surveillance. IEEE Trans Multimedia 20(3):645–658

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3. Liu H, Tian Y, Yang Y et al (2016) Deep relative distance learning: tell the difference between similar vehicles. In: Proceedings of the IEEE conference on computer vision and pattern recognition. IEEE, Las Vegas, pp 2167–2175

4. Lou Y, Bai Y, Liu J et al (2019) Veri-wild: a large dataset and a new method for vehicle re-identification in the wild. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. IEEE, Long Beach, pp 3235–3243

5. Zheng Z, Ruan T, Wei Y et al (2019) VehicleNet: learning robust feature representation for vehicle re-identification. In: The IEEE conference on computer vision and pattern recognition (CVPR) workshops. IEEE, Los Angeles, pp 1–4

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