NTU-ESOS-Capstone topics of Engineering Science and Ocean Engineering

This is an implementation of AI-based Face Anti-Spoofing(FAS) Detection. The goal of this project is to perform FAS detection on Rasberry Pi 4. We trained CDCN++ which was proposed in "Searching Central Difference Convolutional Networks for Face Anti-Spoofing" from scratch. The model was trained on OULU-NPU and SiW dataset.

• 明軒桑's facial depth map

• Run on Rasberry Pi 4

(kind of laggy due to the limited computation resources on Rasberry Pi)

• Run on my laptop

• Weights

  Weights can be acquired here.

• Start detecting!

  $ python run.py --detector_path --model_weights

  Use --detector_path and --model_weights to assign paths.

@inproceedings{yu2020searching,
    title={Searching Central Difference Convolutional Networks for Face Anti-Spoofing},
    author={Yu, Zitong and Zhao, Chenxu and Wang, Zezheng and Qin, Yunxiao and Su, Zhuo and Li, Xiaobai and Zhou, Feng and Zhao, Guoying},
    booktitle= {CVPR},
    year = {2020}
}

@inProceedings{feng2018prn,
  title     = {Joint 3D Face Reconstruction and Dense Alignment with Position Map Regression Network},
  author    = {Yao Feng and Fan Wu and Xiaohu Shao and Yanfeng Wang and Xi Zhou},
  booktitle = {ECCV},
  year      = {2018}
}
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