AnyArtisticGlyph: Multilingual Controllable Artistic Glyph Generation

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 onthis https URLto advance text generation technology.

@article{lu2025_2504.04743,
  title={ AnyArtisticGlyph: Multilingual Controllable Artistic Glyph Generation },
  author={ Xiongbo Lu and Yaxiong Chen and Shengwu Xiong },
  journal={arXiv preprint arXiv:2504.04743},
  year={ 2025 }
}