Detecting Deepfake Talking Heads from Facial Biometric Anomalies
Abstract
The combination of highly realistic voice cloning, along with visually compelling avatar, face-swap, or lip-sync deepfake video generation, makes it relatively easy to create a video of anyone saying anything. Today, such deepfake impersonations are often used to power frauds, scams, and political disinformation. We propose a novel forensic machine learning technique for the detection of deepfake video impersonations that leverages unnatural patterns in facial biometrics. We evaluate this technique across a large dataset of deepfake techniques and impersonations, as well as assess its reliability to video laundering and its generalization to previously unseen video deepfake generators.
Fields of Study & Subjects
Face recognition and analysis
Publication details
- Journal / source
- 2026 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)
- Publisher
- IEEE
- Pages
- 232–240
- Publication date
- 1 March 2026
- Language
- EN