Realism to Deception: Investigating Deepfake Detectors Against Face Enhancement

• URL: http://arxiv.org/abs/2509.07178v1
• Date: Mon, 08 Sep 2025 19:49:52 GMT
• Title: Realism to Deception: Investigating Deepfake Detectors Against Face Enhancement
• Abstract summary: Face enhancement techniques can inadvertently distort biometric features, leading to significant decrease in the accuracy of deepfake detectors.<n>We systematically evaluate whether commonly used face enhancement methods can serve as anti-forensic tools.<n>Our results demonstrate that face enhancement methods can effectively function as anti-forensic tools.
• Score: 1.8886473137668816
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Face enhancement techniques are widely used to enhance facial appearance. However, they can inadvertently distort biometric features, leading to significant decrease in the accuracy of deepfake detectors. This study hypothesizes that these techniques, while improving perceptual quality, can degrade the performance of deepfake detectors. To investigate this, we systematically evaluate whether commonly used face enhancement methods can serve an anti-forensic role by reducing detection accuracy. We use both traditional image processing methods and advanced GAN-based enhancements to evaluate the robustness of deepfake detectors. We provide a comprehensive analysis of the effectiveness of these enhancement techniques, focusing on their impact on Na\"ive, Spatial, and Frequency-based detection methods. Furthermore, we conduct adversarial training experiments to assess whether exposure to face enhancement transformations improves model robustness. Experiments conducted on the FaceForensics++, DeepFakeDetection, and CelebDF-v2 datasets indicate that even basic enhancement filters can significantly reduce detection accuracy achieving ASR up to 64.63\%. In contrast, GAN-based techniques further exploit these vulnerabilities, achieving ASR up to 75.12\%. Our results demonstrate that face enhancement methods can effectively function as anti-forensic tools, emphasizing the need for more resilient and adaptive forensic methods.

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