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Diffusion-based generative models' impressive ability to create convincingimages has captured global attention. However, their complex internalstructures and operations often make them difficult for non-experts tounderstand. We present Diffusion Explainer, the first interactive visualizationtool that explains how Stable Diffusion transforms text prompts into images.Diffusion Explainer tightly integrates a visual overview of Stable Diffusion'scomplex components with detailed explanations of their underlying operations,enabling users to fluidly transition between multiple levels of abstractionthrough animations and interactive elements. By comparing the evolutions ofimage representations guided by two related text prompts over refinementtimesteps, users can discover the impact of prompts on image generation.Diffusion Explainer runs locally in users' web browsers without the need forinstallation or specialized hardware, broadening the public's education accessto modern AI techniques. Our open-sourced tool is available at:https://poloclub.github.io/diffusion-explainer/. A video demo is available athttps://youtu.be/Zg4gxdIWDds.

Diffusion Explainer: Visual Explanation for Text-to-image Stable Diffusion