rustyneuron01/AI-Generated-Content-Detection
Multi-modal AI-generated content detection: image, video, and audio. Benchmarks, training code (DINOv2, DINOv3, ReStraV, BreathNet), and evaluation pipeline for real vs. synthetic classification with calibration-aware metrics.
This project helps anyone who needs to verify the authenticity of digital media. It takes images, videos, or audio files and tells you if they are real (human-captured) or if they were generated or manipulated by AI. This tool is designed for content authenticators, media safety professionals, or researchers needing to distinguish genuine content from synthetic media.
118 stars.
Use this if you need a reliable way to determine whether an image, video, or audio file is authentic or AI-generated, especially for critical applications where trust in media is essential.
Not ideal if you're looking for a simple consumer app or if your primary concern is identifying specific AI generator models rather than a general real-vs-fake distinction.
Stars
118
Forks
69
Language
Python
License
MIT
Category
Last pushed
Mar 13, 2026
Commits (30d)
0
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