WordCraft: Interactive Artistic Typography with Attention Awareness and Noise Blending

• URL: http://arxiv.org/abs/2507.09573v1
• Date: Sun, 13 Jul 2025 10:49:09 GMT
• Title: WordCraft: Interactive Artistic Typography with Attention Awareness and Noise Blending
• Authors: Zhe Wang, Jingbo Zhang, Tianyi Wei, Wanchao Su, Can Wang,
• Abstract summary: Artistic typography aims to stylize input characters with visual effects that are both creative and legible.<n>Traditional approaches rely heavily on manual design, while recent generative models, particularly diffusion-based methods, have enabled automated character stylization.<n>We introduce WordCraft, an interactive artistic typography system that integrates diffusion models to address these limitations.
• Score: 12.655120187133779
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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.

Related papers

• Calligrapher: Freestyle Text Image Customization [72.71919410487881]
  Calligrapher is a novel diffusion-based framework that integrates advanced text customization with artistic typography.<n>By automating high-quality, visually consistent typography, Calligrapher surpasses traditional models.
  arXiv  Detail & Related papers  (2025-06-30T17:59:06Z)
• DesignDiffusion: High-Quality Text-to-Design Image Generation with Diffusion Models [115.62816053600085]
  We present DesignDiffusion, a framework for synthesizing design images from textual descriptions.<n>The proposed framework directly synthesizes textual and visual design elements from user prompts.<n>It utilizes a distinctive character embedding derived from the visual text to enhance the input prompt.
  arXiv  Detail & Related papers  (2025-03-03T15:22:57Z)
• ArtCrafter: Text-Image Aligning Style Transfer via Embedding Reframing [25.610375901522886]
  ArtCrafter is a novel framework for text-to-image style transfer.<n>We introduce an attention-based style extraction module.<n>We also present a novel text-image aligning augmentation component.
  arXiv  Detail & Related papers  (2025-01-03T19:17:27Z)
• VitaGlyph: Vitalizing Artistic Typography with Flexible Dual-branch Diffusion Models [53.59400446543756]
  Artistic typography is a technique to visualize the meaning of input character in an imaginable and readable manner.<n>We introduce a dual-branch, training-free method called VitaGlyph, enabling flexible artistic typography with controllable geometry changes.
  arXiv  Detail & Related papers  (2024-10-02T16:48:47Z)
• MetaDesigner: Advancing Artistic Typography Through AI-Driven, User-Centric, and Multilingual WordArt Synthesis [65.78359025027457]
  MetaDesigner introduces a transformative framework for artistic typography, powered by Large Language Models (LLMs)<n>Its foundation is a multi-agent system comprising the Pipeline, Glyph, and Texture agents, which collectively orchestrate the creation of customizable WordArt.
  arXiv  Detail & Related papers  (2024-06-28T11:58:26Z)
• ORACLE: Leveraging Mutual Information for Consistent Character Generation with LoRAs in Diffusion Models [3.7599363231894185]
  We introduce a novel framework designed to produce consistent character representations from a single text prompt. Our framework outperforms existing methods in generating characters with consistent visual identities.
  arXiv  Detail & Related papers  (2024-06-04T23:39:08Z)
• Dynamic Typography: Bringing Text to Life via Video Diffusion Prior [73.72522617586593]
  We present an automated text animation scheme, termed "Dynamic Typography" It deforms letters to convey semantic meaning and infuses them with vibrant movements based on user prompts. Our technique harnesses vector graphics representations and an end-to-end optimization-based framework.
  arXiv  Detail & Related papers  (2024-04-17T17:59:55Z)
• CreativeSynth: Cross-Art-Attention for Artistic Image Synthesis with Multimodal Diffusion [73.08710648258985]
  Key painting attributes including layout, perspective, shape, and semantics often cannot be conveyed and expressed through style transfer.<n>Large-scale pretrained text-to-image generation models have demonstrated their capability to synthesize a vast amount of high-quality images.<n>Our main novel idea is to integrate multimodal semantic information as a synthesis guide into artworks, rather than transferring style to the real world.
  arXiv  Detail & Related papers  (2024-01-25T10:42:09Z)
• WordArt Designer API: User-Driven Artistic Typography Synthesis with Large Language Models on ModelScope [43.68826200853858]
  This paper introduces the WordArt Designer API, a novel framework for user-driven artistic typography synthesis utilizing Large Language Models (LLMs) on ModelScope. We address the challenge of simplifying artistic typography for non-professionals by offering a dynamic, adaptive, and computationally efficient alternative to traditional rigid templates.
  arXiv  Detail & Related papers  (2024-01-03T12:06:02Z)
• DS-Fusion: Artistic Typography via Discriminated and Stylized Diffusion [10.75789076591325]
  We introduce a novel method to automatically generate an artistic typography by stylizing one or more letter fonts. Our approach utilizes large language models to bridge texts and visual images for stylization and build an unsupervised generative model.
  arXiv  Detail & Related papers  (2023-03-16T19:12:52Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.