StyleAT: Defending Face Recognition Against Semantic Attacks
With face-recognition models now embedded in everyday authentication and surveillance, recent works have pinpointed a critical weakness: these models remain acutely vulnerable to adversarial semantic edits. I.e., adversarially produced semantic alterations to the input, such as slight aging or pose changes, can induce...
Ben Shapira, Roi Cohen, Shang-Tse Chen et al.
· 0 citations