Diffusion models have gained increasing attention for their impressive generation abilities
but currently struggle with rendering accurate and coherent text. To address this issue, we …

Automatic font generation remains a challenging research issue due to the large amounts of
characters with complicated structures. Typically, only a few samples can serve as the …

Few-shot font generation (FFG), which aims to generate a new font with a few examples, is
gaining increasing attention due to the significant reduction in labor cost. A typical FFG …

Content and style disentanglement is an effective way to achieve few-shot font generation. It
allows to transfer the style of the font image in a source domain to the style defined with a …

Generating a new font library is a very labor-intensive and time-consuming job for glyph-rich
scripts. Few-shot font generation is thus required, as it requires only a few glyph references …

Font generation presents a significant challenge due to the intricate details needed,
especially for languages with complex ideograms and numerous characters, such as …

Automatic few-shot font generation (AFFG), aiming at generating new fonts with only a few
glyph references, reduces the labor cost of manually designing fonts. However, the …

Automatic font generation is an imitation task, which aims to create a font library that mimics
the style of reference images while preserving the content from source images. Although …

Few-shot font generation is challenging, as it needs to capture the fine-grained stroke styles
from a limited set of reference glyphs, and then transfer to other characters, which are …

Few-shot font generation (FFG), aiming at generating font images with a few samples, is an
emerging topic in recent years due to the academic and commercial values. Typically, the …