[CVPR 2019] Pytorch codes for Multi-adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection
Pytorch codes for Multi-adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection in CVPR 2019
The framework of the proposed method:
Prerequisites: Python 3.6, pytorch 0.4.0, Numpy, TensorboardX, Pillow, SciPy, h5py
The source code folders:
To run the main file: python main.py --training_type Train
To run the main file: python main.py --training_type Test
It will generate a .h5 file that contains the score for each frame. Then, we use these scores to calculate the AUC and HTER.
Please kindly cite this paper in your publications if it helps your research:
@InProceedings{Shao_2019_CVPR,
author = {Shao, Rui and Lan, Xiangyuan and Li, Jiawei and Yuen, Pong C.},
title = {Multi-Adversarial Discriminative Deep Domain Generalization for Face Presentation Attack Detection},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}
Contact: [email protected]