R2BD: A Reconstruction-Based Method for Generalizable and Efficient Detection of Fake Images

Researchers developed R2BD, a new method to detect fake images created by AI (such as those made by diffusion models, VAEs, or GANs, which are different types of generative AI systems) by reconstructing them and measuring the differences from originals. The method is much faster (over 22 times speedier) than previous approaches because it works in a single step instead of many steps, and it works better across different types of AI image generators and different datasets.