WordCraft: Interactive Artistic Typography with Attention Awareness and Noise Blending

TL;DR

WordCraft is an interactive typography system that combines diffusion models, regional attention, noise blending, and language understanding to enable flexible, high-quality, multi-character stylized text creation with user-driven refinement.

Contribution

It introduces a training-free regional attention mechanism and noise blending for interactive, multi-region typography generation, integrated with language models for flexible prompt interpretation.

Findings

Supports multi-language, multi-character stylization

Enables iterative refinement without quality loss

Enhances interactivity for creative typography design

Abstract

Artistic typography aims to stylize input characters with visual effects that are both creative and legible. Traditional approaches rely heavily on manual design, while recent generative models, particularly diffusion-based methods, have enabled automated character stylization. However, existing solutions remain limited in interactivity, lacking support for localized edits, iterative refinement, multi-character composition, and open-ended prompt interpretation. We introduce WordCraft, an interactive artistic typography system that integrates diffusion models to address these limitations. WordCraft features a training-free regional attention mechanism for precise, multi-region generation and a noise blending that supports continuous refinement without compromising visual quality. To support flexible, intent-driven generation, we incorporate a large language model to parse and structure both concrete and abstract user prompts. These components allow our framework to synthesize high-quality, stylized typography across single- and multi-character inputs across multiple languages, supporting diverse user-centered workflows. Our system significantly enhances interactivity in artistic typography synthesis, opening up creative possibilities for artists and designers.