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arXiv · 2504.04743

AnyArtisticGlyph: Multilingual Controllable Artistic Glyph Generation

Xiongbo Lu·Yaxiong Chen·Shengwu Xiong
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Abstract

Artistic Glyph Image Generation (AGIG) differs from current creativity-focused generation models by offering finely controllable deterministic generation. It transfers the style of a reference image to a source while preserving its content. Although advanced and promising, current methods may reveal flaws when scrutinizing synthesized image details, often producing blurred or incorrect textures, posing a significant challenge. Hence, we introduce AnyArtisticGlyph, a diffusion-based, multilingual controllable artistic glyph generation model. It includes a font fusion and embedding module, which generates latent features for detailed structure creation, and a vision-text fusion and embedding module that uses the CLIP model to encode references and blends them with transformation caption embeddings for seamless global image generation. Moreover, we incorporate a coarse-grained feature-level loss to enhance generation accuracy. Experiments show that it produces natural, detailed artistic glyph images with state-of-the-art performance. Our project will be open-sourced on https://github.com/jiean001/AnyArtisticGlyph to advance text generation technology.

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Xiongbo Lu, Yaxiong Chen, Shengwu Xiong. 2025-04-07. AnyArtisticGlyph: Multilingual Controllable Artistic Glyph Generation. https://arxiv.org/abs/2504.04743

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