Script for fine-tuning our FSFM-3C model for MCIO LOO evaluation of cross-domain face anti-spoofing:
==============OCI2M==============
CUDA_VISIBLE_DEVICES=0 python train_vit.py \
--pt_model ../../pretrain/checkpoint/pretrained_models/VF2_ViT-B/checkpoint-400.pth \
--op_dir ./checkpoint/finetuned_models/MCIO_protocol/OCI2M/ \
--report_logger_path ./checkpoint/finetuned_models/MCIO_protocol/OCI2M/performance.csv \
--config M \
==============OMI2C==============
CUDA_VISIBLE_DEVICES=0 python train_vit.py \
--pt_model ../../pretrain/checkpoint/pretrained_models/VF2_ViT-B/checkpoint-400.pth \
--op_dir ./checkpoint/finetuned_models/MCIO_protocol/OMI2C/ \
--report_logger_path ./checkpoint/finetuned_models/MCIO_protocol/OMI2C/performance.csv \
--config C \
==============OCM2I==============
CUDA_VISIBLE_DEVICES=3 python train_vit.py \
--pt_model ../../pretrain/checkpoint/pretrained_models/VF2_ViT-B/checkpoint-400.pth \
--op_dir ./checkpoint/finetuned_models/MCIO_protocol/OCM2I/ \
--report_logger_path ./checkpoint/finetuned_models/MCIO_protocol/OCM2I/performance.csv \
--config I \
==============ICM2O==============
CUDA_VISIBLE_DEVICES=3 python train_vit.py \
--pt_model ../../pretrain/checkpoint/pretrained_models/VF2_ViT-B/checkpoint-400.pth \
--op_dir ./checkpoint/finetuned_models/MCIO_protocol/ICM2O/ \
--report_logger_path ./checkpoint/finetuned_models/MCIO_protocol/ICM2O/performance.csv \
--config O \