A two-phase framework with full-face style-invariant modeling and attention-guided patch subnetworks detects disguise makeup attacks, achieving 8.97% ACER on a new dataset and strong results on SIW-Mv2.
One-Class Face Anti-spoofing via Spoof Cue Map-Guided Feature Learning,
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Generalized Disguise Makeup Presentation Attack Detection Using an Attention-Guided Patch-Based Framework
A two-phase framework with full-face style-invariant modeling and attention-guided patch subnetworks detects disguise makeup attacks, achieving 8.97% ACER on a new dataset and strong results on SIW-Mv2.