Generate by Low_level_features_visualization.py
grad_cam==1.3.5
matplotlib==3.5.2
numpy==1.22.3
scikit_learn==1.1.2
torch==1.12.0
torchvision==0.13.0
Step 1: run Amap_train.py
to get pretrained model for producing activation map
Step 2: run train.py
to train LDCNet
run test.py
If you use the LDC, please cite the paper:
@article{huang2022learnable,
title={Learnable Descriptive Convolutional Network for Face Anti-Spoofing},
author={Huang, Pei-Kai and Ni, Hui-Yu and Ni, Yan-Qin and Hsu, Chiou-Ting},
year={2022}
}
We are students from MPLAB at National Tsing Hua University.
Huang, Pei-Kai alwayswithme@gapp.nthu.edu.tw
Ni, Hui-Yu huiyu8794@gmail.com
Chong, Jun-Xiong jxchong99@gmail.com