Pretrained DeiT-S Vision Transformer reaches 97.27% accuracy and cuts ethnic ACER gap to 0.13% on CeFA dataset while showing 3.6x better zero-shot generalization than ResNet18 CNN.
Introduc- tion to Presentation Attack Detection in Face Biometrics and Recent Advances,
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Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks
Pretrained DeiT-S Vision Transformer reaches 97.27% accuracy and cuts ethnic ACER gap to 0.13% on CeFA dataset while showing 3.6x better zero-shot generalization than ResNet18 CNN.