Improving generalization to unseen scenarios is one of the greatest challenges in Face Anti-spoofing (FAS). Most previous FAS works focus on domain debiasing to eliminate the distribution discrepancy between training a...
Improving generalization to unseen scenarios is one of the greatest challenges in Face Anti-spoofing (FAS). Most previous FAS works focus on domain debiasing to eliminate the distribution discrepancy between training and test data. However, a crucial but usually neglected bias factor is the face ide...