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OADE-Net


Original and attention-guided DenseNet-based ensemble network for person re-identification using infrared light images system. Any works that uses the provided pretrained network must acknowledge the authors by including the following reference.

Min Su Jeong, Seong In Jeong, Seon Jong Kang, Kyung Bong Ryu, and Kang Ryoung Park, “OADE-Net: Original and Attention-guided DenseNet-based Ensemble Network for Person Re-identification Using Infrared Light Images,” Mathematics, In submission 


Download trained model

https://drive.google.com/file/d/1DphKtdPyLQwLrDoEezZE0qNNRqq0QAga/view?usp=sharing

Download thermal database

https://drive.google.com/file/d/1ugIeeHM0OTWhgNeF4ftP4AKE7s7ltYww/view?usp=sharing (DBPerson-Recog-DB1_thermal [1])

You can download SYSU-MM01 https://github.com/wuancong/SYSU-MM01 [2]


Prerequisites

  • python 3.8.8
  • pytorch 1.8.1
  • Windows 10

Reference

  • [1] Nguyen, D.T.; Hong, H.G.; Kim, K.W.; Park, K.R. Person recognition system based on a combination of body images from visible light and thermal cameras. Sensors, 2017. 17(3): p. 605.

  • [2] Wu, A.; Zheng, W.-S.; Gong, S.; Lai, J. RGB-IR person re-identification by cross-modality similarity preservation. Int. J. Comput. Vis., 2020, 128; pp. 1765-1785.

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