yizhe-ang/fake-detection-lab

Media Forensics / Fake Detection experiments in PyTorch. Implements Fighting Fake News: Image Splice Detection via Learned Self-Consistency

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Experimental

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.

media-forensics image-authenticity fake-news-detection digital-splicing visual-content-verification
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 4 / 25

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Stars

25

Forks

1

Language

Jupyter Notebook

License

MIT

Last pushed

Sep 19, 2021

Commits (30d)

0

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