VecDesigner: Exploring Visual Guidance and Structural Consistency for Semantic Typography

Semantic Typography aims to visualize the meaning of an input word through the form of a character, while preserving its legibility. Existing vector-based methods, which primarily rely on text-driven optimization like Score Distillation Sampling (SDS), often produce glyphs that lack rich semantic details. Furthermore, these approaches struggle to maintain the overall structural integrity of the glyphs and frequently suffer from visual artifacts caused by intersections, compromising both readability and aesthetic quality. To address these challenges, we propose VecDesigner, a novel optimization-based method for vector semantic typography. Specifically, we introduce Visual-Guided Score Distillation Sampling (VGSDS), which leverages text-related reference images as visual guidance to infuse the glyphs with richer and more concrete semantic details. To preserve legibility and structural integrity, we design a vector-based Procrustes loss to constrain the overall deformation of the glyph. Concurrently, we effectively mitigate the intersection problem by imposing positional relationship constraints on the control points. Comprehensive experiments demonstrate that VecDesigner outperforms existing methods in both semantic expression and structural preservation, generating high-quality, expressive, and clearly legible semantic glyphs.

Semantic typography transforms words into visual art that reflects their meaning (like making the letters in "cat" look furry), but current automated methods often fall short. Existing tools tend to produce designs that lack rich details, create messy overlapping lines, or warp the letters so much that the original word becomes unreadable. To solve this, we developed VecDesigner, a new system that uses reference images, rather than just text prompts, to guide the design process, infusing the letters with highly detailed and realistic features. We also introduced specific mathematical rules to limit how much the letters can bend and to prevent lines from improperly crossing, ensuring the core shape of the text remains intact. Our approach successfully balances creative artistic expression with structural integrity. This research matters because it empowers designers and everyday users to automatically generate high-quality, expressive word art that clearly communicates a visual concept without ever sacrificing legibility.