HR-Font: Cross-Script Font Generation via Realization Priors and Appearance Completion

We introduce HR-Font, a framework for extending a typeface to new scripts from a few Chinese reference glyphs. The central challenge is to translate a family’s visual language into characters whose structures differ from those observed. HR-Font addresses this challenge through two complementary forms of conditioning. The Character Realization Prior (CRP) represents same-character examples from a font bank as variations relative to neutral content and uses them to condition spatial deformation in the denoiser. Target-character appearance completion reads multi-scale local reference features to predict a spatial appearance representation of the requested glyph, supervised by training-target features. The resulting conditions guide a diffusion generator toward recognizable characters with a coherent family identity. We evaluate paired reconstruction and cross-script reference-style consistency on 47 fonts across Latin, kana, and Bopomofo. In a blinded Latin-character study with 28 designers and domain experts, HR-Font is the highest-ranked generated method, with a 77.5% Top-2 inclusion rate.