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.
A team of researchers has developed a computer program that creates realistic videos that reflect the facial expressions and head movements of the person speaking, only requiring an audio clip and a face photo. DIverse yet Realistic Facial Animations, or DIRFA, is an artificial intelligence-based program that takes audio…
Humans pay enormous attention to lips during conversation, and robots have struggled badly to keep up. A new robot developed at Columbia Engineering learned realistic lip movements by watching its own reflection and studying human videos online. This allowed it to speak and sing with synchronized facial motion, without being…