Detecting Deepfake Talking Heads from Facial Biometric Anomalies

• URL: http://arxiv.org/abs/2507.08917v1
• Date: Fri, 11 Jul 2025 16:29:25 GMT
• Title: Detecting Deepfake Talking Heads from Facial Biometric Anomalies
• Authors: Justin D. Norman, Hany Farid,
• Abstract summary: Deepfake video impersonations are often used to power frauds, scams, and political disinformation.<n>We propose a novel machine learning technique for the detection of deepfake video impersonations that leverages unnatural patterns in facial biometrics.<n>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.
• Score: 12.369423169349673
• License: http://creativecommons.org/licenses/by/4.0/
• 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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