  Generative adversary network (GAN) generated high-realistic human faces have
been used as profile images for fake social media accounts and are visually
challenging to discern from real ones. In this work, we show that GAN-generated
faces can be exposed via irregular pupil shapes. This phenomenon is caused by
the lack of physiological constraints in the GAN models. We demonstrate that
such artifacts exist widely in high-quality GAN-generated faces and further
describe an automatic method to extract the pupils from two eyes and analysis
their shapes for exposing the GAN-generated faces. Qualitative and quantitative
evaluations of our method suggest its simplicity and effectiveness in
distinguishing GAN-generated faces.
