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arXiv · 2507.08917

Detecting Deepfake Talking Heads from Facial Biometric Anomalies

Justin D. Norman·Hany Farid
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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.

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Justin D. Norman, Hany Farid. 2025-07-11. Detecting Deepfake Talking Heads from Facial Biometric Anomalies. https://arxiv.org/abs/2507.08917

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