Deep fakes, falsification of reality - Hello Future Orange

A threat to democracy (manipulation of public opinion, aggravation of social or community-based tensions, etc.), invasion of a person's privacy or violation of their dignity, a risk of fraud or scams, or still a headache for future researchers seeking the truth, etc. Deep fakes, technologies that make it possible to replace someone's face with that of another person in a video thanks to deep learning, are worrying. Ever more sophisticated, today they are pretty much available to all thanks to relatively easy-to-use tools. A chat about these "weapons of mass falsification" with Vincent Nozick, a teacher and researcher at the LIGM and co-author of a publication presenting an efficient method to detect deep fakes (MesoNet: a Compact Facial Video Forgery Detection Network, Darius Afchar, Vincent Nozick, Junichi Yamagishi, Isao Echizen, 2018). There are several methods for tampering with faces, some of which do use deep learning, like Deepfake, which is one of the most well-known. Deepfake is a program that belongs to the GAN family, Generative Adversarial Networks, and makes it possible to transfer facial expressions onto video. It is based on an autoencoder, which is made up of an encoder and a decoder.