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

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

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 …

Handwritten text recognition and Word Retrieval, also known as Word Spotting, are
traditional problems in the document analysis community. While the use of increasingly …

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 …

Handwritten mathematical expression recognition (HMER) poses a formidable challenge
due to the intricate two-dimensional structures and diverse handwriting styles. This paper …

The generation of images of realistic looking, readable handwritten text is a challenging task
which is referred to as handwritten text generation (HTG). Given a string and examples from …

The ability to generate realistic synthetic text lines is crucial for training robust handwritten
text recognition models when there is a scarcity of annotated training data. Existing …

–In Appendix A, we discuss several similar works, and review the related work of diffusion
methods in general image generation.–In Appendix B, we describe more method details …