PeterWang512/CNNDetection

Health v2 · maintenance only

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Adoption not part of the score

1005 stars · 185 forks observed · 2026-09-03

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A PyTorch research codebase with pretrained models for detecting CNN-generated (GAN/synthetic) images, from the CVPR 2020 paper 'CNN-generated images are surprisingly easy to spot...for now'. It includes demo scripts for single images and datasets, plus training and evaluation code and the paper's dataset.

Use cases

• detect if an image was generated by a GAN
• evaluate a fake-image detector on a real/fake dataset
• train a CNN-generated image detector
• test robustness of synthetic image detection against JPEG and blur
• benchmark detection on StyleGAN3 outputs

When to choose

• you need a pretrained detector for GAN-generated images
• you want to reproduce or extend CVPR 2020 synthetic image detection research
• you need AP/accuracy evaluation on a real-vs-fake image directory

When to avoid

• you need detection of diffusion-model images rather than CNN/GAN-generated ones
• you want a production-ready API or service rather than research code
• you need a permissively licensed library - the license is non-standard

Facets

library · maturity maintenance

machine-learning computer-vision image-processing testing computer-vision image-processing deep-learning artificial-intelligence python windows deepfake-detection gan-detection synthetic-image-detection pytorch cvpr-2020 research-code pretrained-models linux macos gpu

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