Existing handwritten text generation methods often require more than ten handwriting
samples as style references. However, in practical applications, users tend to prefer a …

Handwriting synthesis, the task of automatically generating realistic images of handwritten
text, has gained increasing attention in recent years, both as a challenge in itself, as well as …

Recently, with the rapid advancements of generative models, the field of visual text
generation has witnessed significant progress. However, it is still challenging to render high …

Handwriting, as a uniquely human skill, contributes to fine motor development and cognitive
growth. Beyond mere functionality, handwriting carries individuality and subtle emotional …

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 …

Recently, continuous diffusion models (CDM) have been introduced into non-autoregressive
(NAR) text-to-text generation. However, the discrete nature of text increases the difficulty of …

Abstract Handwritten Text Generation (HTG) conditioned on text and style is a challenging
task due to the variability of inter-user characteristics and the unlimited combinations of …

With the advancement of deep learning-based character recognition models, the training
data size has become a crucial factor in improving the performance of handwritten text …

The imitation of cursive handwriting is mainly limited to generating handwritten words or
lines. Multiple synthetic outputs must be stitched together to create paragraphs or whole …

With the progress of artificial intelligence generated content (AIGC) technologies, style-
controlled image generation methods based on diffusion models have shown promising …