Nikolay Sergievskiy, Roman Vlasov, Roman Trusov
This is the official implementation of the paper Generalizable Method for Face Anti-Spoofing with Semi-Supervised Learning by the ML research team from Entry
This work is done using a proprietary dataset, which is why we cannot share the data or pretrained models.
We use WandB for model comparison and monitoring, and the training/validation script relies on it heavily, so by default you will need an account to export results there.
code/train_config.yaml- main configuration for training/evalcode/run.py- training/validation script with CLIcode/dataset- package with utilities for loading and augmenting datacode/entry_antispoof- package with utils, loss functions, and network definitions