yizhe-ang/fake-detection-lab
Media Forensics / Fake Detection experiments in PyTorch. Implements Fighting Fake News: Image Splice Detection via Learned Self-Consistency
This project helps media analysts, journalists, and forensic investigators determine if an image has been manipulated. You input an image, and the system evaluates it to detect signs of digital splicing, indicating potential fakery. It's designed for professionals who need to verify the authenticity of visual content.
No commits in the last 6 months.
Use this if you need to perform experiments in fake image detection, specifically for identifying spliced images, and want to evaluate detection models with and without adversarial attacks.
Not ideal if you're looking for a user-friendly application for quick, one-off image verification without delving into model training or configuration.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Sep 19, 2021
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