Misleading Deep-Fake Detection with GAN Fingerprints. (arXiv:2205.12543v1 [cs.CV])

Generative adversarial networks (GANs) have made remarkable progress in
synthesizing realistic-looking images that effectively outsmart even humans.
Although several detection methods can recognize these deep fakes by checking
for image artifacts from the generation process, multiple counterattacks have
demonstrated their limitations. These attacks, however, still require certain
conditions to hold, such as interacting with the detection method or adjusting
the GAN directly. In this paper, we introduce a novel class of simple
counterattacks that overcomes these limitations. In particular, we …

arxiv cv detection fake gan