awsaf49/artifact

[ICIP 2023] ArtiFact: A Large-Scale Dataset with Artificial (Fake) and Factual (Real) Images for Generalizable and Robust Synthetic Image Detection

27
/ 100
Experimental

This dataset helps security analysts, content moderators, and digital forensics specialists detect images generated by AI. It provides a vast collection of both authentic and AI-generated images, covering diverse categories like human faces, animals, and places. You get images along with labels indicating whether each is real or fake, enabling you to build and test robust fake image detection systems.

No commits in the last 6 months.

Use this if you need to train or evaluate a system that can reliably identify AI-generated images, especially when facing new or previously unseen AI generators.

Not ideal if your primary need is to generate new AI images, as this project focuses solely on detection.

digital-forensics content-moderation image-authenticity deepfake-detection AI-image-detection
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 8 / 25
Community 10 / 25

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Language

Python

License

Last pushed

May 24, 2024

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