Dual Frequency Branch Framework With Reconstructed Sliding Windows Attention for AI-Generated Image Detection

This paper describes a new method for detecting AI-generated images (images created by GANs, which are machine learning models that generate synthetic images, or diffusion models, which gradually refine noise into images) by analyzing images in multiple frequency domains (different ways of breaking down an image into mathematical components) using attention mechanisms (techniques that help AI focus on important parts of data). The approach achieved better detection accuracy than previous methods when tested on images from 65 different generative models.