  AI-based image generation has continued to rapidly improve, producing
increasingly more realistic images with fewer obvious visual flaws.
AI-generated images are being used to create fake online profiles which in turn
are being used for spam, fraud, and disinformation campaigns. As the general
problem of detecting any type of manipulated or synthesized content is
receiving increasing attention, here we focus on a more narrow task of
distinguishing a real face from an AI-generated face. This is particularly
applicable when tackling inauthentic online accounts with a fake user profile
photo. We show that by focusing on only faces, a more resilient and
general-purpose artifact can be detected that allows for the detection of
AI-generated faces from a variety of GAN- and diffusion-based synthesis
engines, and across image resolutions (as low as 128 x 128 pixels) and
qualities.
