VitaGlyph: Vitalizing Artistic Typography with Flexible Dual-branch Diffusion Models (2410.01738v2)

Abstract: Artistic typography is a technique to visualize the meaning of input character in an imaginable and readable manner. With powerful text-to-image diffusion models, existing methods directly design the overall geometry and texture of input character, making it challenging to ensure both creativity and legibility. In this paper, we introduce a dual-branch and training-free method, namely VitaGlyph, enabling flexible artistic typography along with controllable geometry change to maintain the readability. The key insight of VitaGlyph is to treat input character as a scene composed of Subject and Surrounding, followed by rendering them under varying degrees of geometry transformation. The subject flexibly expresses the essential concept of input character, while the surrounding enriches relevant background without altering the shape. Specifically, we implement VitaGlyph through a three-phase framework: (i) Knowledge Acquisition leverages LLMs to design text descriptions of subject and surrounding. (ii) Regional decomposition detects the part that most matches the subject description and divides input glyph image into subject and surrounding regions. (iii) Typography Stylization firstly refines the structure of subject region via Semantic Typography, and then separately renders the textures of Subject and Surrounding regions through Controllable Compositional Generation. Experimental results demonstrate that VitaGlyph not only achieves better artistry and readability, but also manages to depict multiple customize concepts, facilitating more creative and pleasing artistic typography generation. Our code will be made publicly at https://github.com/Carlofkl/VitaGlyph.

• The paper presents VitaGlyph, a dual-branch diffusion model that revitalizes artistic typography by separating subject and surrounding elements.
• Methodology uses LLM-powered knowledge acquisition and regional decomposition to generate detailed, semantically styled glyphs.
• Experimental results demonstrate improved creativity and readability, offering flexible control over typographic design.

The paper "VitaGlyph: Vitalizing Artistic Typography with Flexible Dual-branch Diffusion Models" presents an innovative approach to artistic typography. The authors introduce VitaGlyph, a dual-branch, training-free method designed to enhance creativity in typography without compromising readability. This method targets the challenge of balancing creativity and legibility when using text-to-image diffusion models to design the geometry and texture of characters.

Key Concepts and Methodology:

1. Scene Composition: VitaGlyph sees each input character as a scene divided into two components: the Subject and the Surrounding. The Subject conveys the essential concept of the character, while the Surrounding provides context and enriches the scene, ensuring the character's shape remains unaltered.
2. Three-Phase Framework:

• Knowledge Acquisition: This phase uses LLMs to generate descriptive text for both the Subject and Surrounding. This helps in designing a more meaningful and context-rich representation of the character.
• Regional Decomposition: This involves detecting parts of the input glyph image that most closely match the Subject description and dividing it into Subject and Surrounding regions.
• Typography Stylization: In this phase, the structure of the Subject region is refined through a process called Semantic Typography. The textures of both Subject and Surrounding regions are then rendered separately using Controllable Compositional Generation, allowing for precise and creative control.

Experimental Results:

The authors demonstrate that VitaGlyph not only improves artistic expression and readability but also supports the depiction of multiple customized concepts. This makes the typography generation more creative and aesthetically pleasing.

Conclusion:

VitaGlyph is a noteworthy advancement in artistic typography. Its dual-branch approach and use of LLMs for knowledge acquisition provide significant flexibility and control over typography design. The method's ability to separate and independently stylize different aspects of a glyph allows for a creative yet readable output. The authors also plan to release their code publicly, enhancing accessibility and potential for further research in this domain.