deepfake-detection

SKILL.md

Comprehensive framework for detecting synthetic media, analyzing manipulation artifacts, and establishing media provenance in the post-empirical era.

Deepfakes are synthetic media created using deep learning techniques—primarily Generative Adversarial Networks (GANs), Diffusion Models, and Autoencoders—to generate or manipulate audiovisual content with a high degree of realism. The term combines "deep learning" and "fake."

| Face Swap | Autoencoders, GANs | Replace one person's face with another in video | | Face Reenactment | 3D Morphable Models | Animate a face with another person's expressions | | Voice Clone | Text-to-Speech, Vocoder | Generate speech in someone's voice from text [[20]](#references) |

Multimodal media authentication and deepfake forensics. PRNU analysis, IGH classification, DQ detection, semantic forensics, and LLM-augmented sensemaking for the post-empirical era. Source: dirnbauer/webconsulting-skills.

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