Training machines to synthesize diverse handwritings is an intriguing task. Recently, RNN-
based methods have been proposed to generate stylized online Chinese characters …

Given limited handwriting scripts, humans can easily visualize (or imagine) what the
handwritten words/texts would look like with other arbitrary textual contents. Moreover, a …

Automatically writing stylized Chinese characters is an attractive yet challenging task due to
its wide applicabilities. In this paper, we propose a novel framework named Style-Aware …

We propose a novel transformer-based styled handwritten text image generation approach,
HWT, that strives to learn both style-content entanglement as well as global and local style …

Humans remain far better than machines at learning, where humans require fewer examples
to learn new concepts and can use those concepts in richer ways. Take handwriting as an …

Despite the latest transcription accuracies reached using deep neural network architectures,
handwritten text recognition still remains a challenging problem, mainly because of the large …

Generating synthetic images of handwritten text in a writer-specific style is a challenging
task, especially in the case of unseen styles and new words, and even more when these …

Representing a space of handwriting stroke styles includes the challenge of representing
both the style of each character and the overall style of the human writer. Existing VRNN …

This paper presents a GAN for generating images of handwritten lines conditioned on
arbitrary text and latent style vectors. Unlike prior work, which produce stroke points or single …

Calligraphy imitation (CI) from a handful of target handwriting samples is such a challenging
task that most of the existing writing style analysis or handwriting generation methods do not …