Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Data. (arXiv:2007.08457v7 [cs.CR] UPDATED)

Photorealistic image generation has reached a new level of quality due to the
breakthroughs of generative adversarial networks (GANs). Yet, the dark side of
such deepfakes, the malicious use of generated media, raises concerns about
visual misinformation. While existing research work on deepfake detection
demonstrates high accuracy, it is subject to advances in generation techniques
and adversarial iterations on detection countermeasure techniques. Thus, we
seek a proactive and sustainable solution on deepfake detection, that is
agnostic to the evolution of …

artificial attribution data deepfake fingerprinting training