Methods of Deepfake Detection Based on Machine Learning
Artem A. Maksutov, Viacheslav O. Morozov, Aleksander A. Lavrenov, Alexander S. Smirnov
Abstract
Nowadays, people faced an emerging problem of AI-synthesized face swapping videos, widely known as the DeepFakes. This kind of videos can be created to cause threats to privacy, fraudulence and so on. Sometimes good quality DeepFake videos recognition could be hard to distinguish with people eyes. That's why researchers need to develop algorithms to detect them. In this work, we present overview of indicators that can tell us about the fact that face swapping algorithms were used on photos. Main purpose of this paper is to find algorithm or technology that can decide whether photo was changed with DeepFake technology or not with good accuracy.
Topics & Concepts
Computer scienceFace (sociological concept)Artificial intelligenceMachine learningQuality (philosophy)Work (physics)Data scienceFacial recognition systemPattern recognition (psychology)SociologyEpistemologyEngineeringPhilosophyMechanical engineeringSocial scienceDigital Media Forensic DetectionGenerative Adversarial Networks and Image SynthesisFace recognition and analysis