The code repo for the paper "Learning a Spoof Pattern Generation Network with Identity Disentanglement for Semi-Supervised Cross-Domain Face Anti-Spoofing"

The network architecture of the proposed S²PLN method:

• Release training and inference code.
• Release pretrained models.

• python 3.7
• pytorch 1.7.1
• torchvision 0.8.2
• cuda 11.0

To install the required packages, you can run pip install -r requirements.txt

Download the OULU-NPU(O), CASIA-FASD(C), Idiap Replay-Attack(I), MSU-MFSD(M), MS-Celeb- 1M and LFW datasets

All video frames of the four datasets are pre-processed with the MTCNN algorithm to perform face detection and cropping, and the cropped RGB face images are resized to 224 × 224 × 3.

To generate the data label list, you can run the following command:

python datalabel/generate_label.py

We would like to express our gratitude to SSDG, which are of great help to our work.