Facial movement analysis detects deepfake videos with more than 95% accuracy

So-called deepfakes, that is, images and videos generated with the help of artificial intelligence, are becoming increasingly difficult to detect. An international research team from the University of Tokyo and the Max Planck Institute for Informatics in Saarbrücken, Germany, has developed a method that identifies manipulated videos more reliably than previous approaches—not by searching for visual artifacts, but by analyzing the naturalness of facial expressions. In tests on established benchmark datasets, the approach achieved an average detection accuracy of more than 95 percent and successfully identified manipulations that caused many existing detectors to fail.