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PoreNet

PyTorch demo code of High-resolution Face Recognition via Deep Pore-feature Matching.

Demo

  1. Run the demo.ipynb notebook on your local machines
  2. Colab demo for PoreNet google colab logo

Example result

result

Citation

If you find this work useful for your research, please consider cite our paper:

@inproceedings{lai2019high,
  title={High-resolution Face Recognition via Deep Pore-feature Matching},
  author={Lai, Shun-Cheung and Kong, Minna and Lam, Kin-Man and Li, Dong},
  journal={IEEE International Conference on Image Processing},
  pages={1173-1177},
  year={2019},
  month={Sep.}
}

Requirements

  • Python3, and install the required libraries using pip.
pip install -r requirements.txt

Reference

  • GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence: code and paper