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

TL;DR

Diffusion Explainer is an interactive visualization tool that helps non-experts understand how Stable Diffusion converts text prompts into images, enhancing learning through visual explanations and comparative analysis.

Contribution

It is the first tool to visually explain the complex operations of Stable Diffusion, making diffusion models more accessible to non-experts.

Findings

User study shows substantial learning benefits for non-experts.

Over 10,300 users from 124 countries have used the tool.

The tool effectively demonstrates the impact of keyword changes on image generation.

Abstract

Diffusion-based generative models' impressive ability to create convincing images has garnered global attention. However, their complex structures and operations often pose challenges for non-experts to grasp. We present Diffusion Explainer, the first interactive visualization tool that explains how Stable Diffusion transforms text prompts into images. Diffusion Explainer tightly integrates a visual overview of Stable Diffusion's complex structure with explanations of the underlying operations. By comparing image generation of prompt variants, users can discover the impact of keyword changes on image generation. A 56-participant user study demonstrates that Diffusion Explainer offers substantial learning benefits to non-experts. Our tool has been used by over 10,300 users from 124 countries at https://poloclub.github.io/diffusion-explainer/.