Recovering Real Faces from Face-Generation ML System
New paper: “This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces.
Abstract: Recently, generative adversarial networks (GANs) have achieved stunning realism, fooling even human observers. Indeed, the popular tongue-in-cheek website http://thispersondoesnotexist.com, taunts users with GAN generated images that seem too real to believe. On the other hand, GANs do leak information about their training data, as evidenced by membership attacks recently demonstrated in the literature. In this work, we challenge the assumption that GAN faces really are novel creations, by constructing a successful membership attack of a new kind. Unlike previous works, our attack can accurately discern samples sharing the same identity as training samples without being the same samples. We demonstrate the interest of our attack across several popular face datasets and GAN training procedures. Notably, we show that even in the presence of significant dataset diversity, an over represented person can pose a privacy concern.
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Jeff • October 14, 2021 2:02 PM
I’m not sure if this is a weakness in the generation algorithm, or just that website. But I have yet to see ThisPersonDoesNotExist generate someone ugly. Compare the ratio of pretty to ugly faces on the street or at a mall with that site. I think there’s a built-in bias somewhere.