CVJul 19

VecFontLLM: Anchor-Guided Direct Synthesis of Chinese Vector Fonts

arXiv:2607.1725111.8
Predicted impact top 27% in CV · last 90 daysOriginality Highly original
AI Analysis

This work solves the long-standing challenge of directly generating complex Chinese vector fonts, enabling efficient font design for typographers and designers.

VecFontLLM introduces an anchor-guided multimodal large language model for direct few-shot synthesis of Chinese vector fonts, achieving high-quality vector glyph generation without raster intermediates. It outperforms existing vector methods and matches raster-domain quality.

Direct generation of Chinese vector fonts is a challenging and ongoing problem. A Chinese vector glyph contains complex component structure, anchor layout, and Bézier curve details, which work at different scales, but a standard vector sequence writes them together in one long sequence, making the task of vector font synthesis challenging. Existing direct vector generators often fail on complex characters, while raster-domain methods must vectorize the synthesized glyph images afterward. To address the above-mentioned problem, this paper proposes VecFontLLM, an anchor-guided multimodal large language model for direct few-shot synthesis of Chinese vector fonts. Our key idea is to generate vector glyphs through anchors rather than a standard vector sequence. Specifically, the proposed VecFontLLM first predicts and refines an anchor scaffold that fixes the coarse layout of components and contours, and then completes Bézier control points to recover local curvature and style. At test time, a confidence-guided generation chain samples multiple component candidates and continues synthesis from the highest-confidence one, improving stability for complex glyphs. This work demonstrates, for the first time, high-quality few-shot synthesis of complex Chinese vector glyphs directly in the vector domain, without raster generation or vectorization. Experiments on several Chinese font datasets show substantial improvements over existing vector font synthesis methods, competitive glyph rendering quality against raster-domain baselines, and vector command distributions close to real fonts.

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