- Conda
- CUDA=11.6
git clone https://github.com/BOVIFOCR/CDCN_FAS.git
cd CDCN_FAS
export CONDA_ENV=bjgbiesseck_cdcn_py39
conda create -y -n $CONDA_ENV python=3.9
conda activate $CONDA_ENV
conda env config vars set CUDA_HOME="/usr/local/cuda-11.6"; conda deactivate; conda activate $CONDA_ENV
conda env config vars set LD_LIBRARY_PATH="$CUDA_HOME/lib64"; conda deactivate; conda activate $CONDA_ENV
conda env config vars set PATH="$CUDA_HOME:$CUDA_HOME/bin:$LD_LIBRARY_PATH:$PATH"; conda deactivate; conda activate $CONDA_ENV
conda install -y pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia
conda install -y -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -y -c bottler nvidiacub
conda install -y pytorch3d -c pytorch3d
pip3 install -r requirements.txt
cd CVPR2020_paper_codes
export CUDA_VISIBLE_DEVICES=0; python train_CDCN_1RandomFrame.py
Main code of CVPR2020 paper "Searching Central Difference Convolutional Networks for Face Anti-Spoofing"
Based on the Central Difference Convolution (CDC) and Contrastive Depth Loss (CDL), we achieved
1st Place in ChaLearn Multi-Modal Face Anti-spoofing Attack Detection Challenge @CVPR2020
2nd Place in ChaLearn Single-Modal(RGB) Face Anti-spoofing Attack Detection Challenge @CVPR2020
It is just for research purpose, and commercial use is not allowed.
If you use the CDC, D-CDC or CDL, please cite these six papers:
@inproceedings{yu2020nasfas,
title={NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofing},
author={Yu, Zitong and Wan, Jun and Qin, Yunxiao and Li, Xiaobai and Li, Stan Z. and Zhao, Guoying},
booktitle= {TPAMI},
year = {2020}
}
@inproceedings{yu2021dual,
title={Dual-Cross Central Difference Network for Face Anti-Spoofing},
author={Yu, Zitong and Qin, Yunxiao and Zhao, Hengshuang and Li, Xiaobai and Zhao, Guoying},
booktitle= {IJCAI},
year = {2021}
}
@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{yu2020face,
title={Face Anti-spoofing with Human Material Perception},
author={Yu, Zitong and Li, Xiaobai and Niu, Xuesong and Shi, Jingang and Zhao, Guoying},
booktitle= {ECCV},
year = {2020}
}
@inproceedings{wang2020deep,
title={Deep Spatial Gradient and Temporal Depth Learning for Face Anti-spoofing},
author={Wang, Zezheng and Yu, Zitong and Zhao, Chenxu and Zhu, Xiangyu and Qin, Yunxiao and Zhou, Qiusheng and Zhou, Feng and Lei, Zhen},
booktitle= {CVPR},
year = {2020}
}
@inproceedings{qin2019learning,
title={Learning Meta Model for Zero-and Few-shot Face Anti-spoofing},
author={Qin, Yunxiao and Zhao, Chenxu and Zhu, Xiangyu and Wang, Zezheng and Yu, Zitong and Fu, Tianyu and Zhou, Feng and Shi, Jingping and Lei, Zhen},
booktitle= {AAAI},
year = {2020}
}