Automatic Generation of Chinese Handwriting via Fonts Style Representation Learning

TL;DR

This paper introduces an end-to-end deep learning system for Chinese font generation that interpolates style embeddings to create new fonts, improving efficiency and style transition smoothness.

Contribution

The paper presents a novel deep learning approach for Chinese font generation using style embedding interpolation, which is simpler and more effective than previous methods.

Findings

Achieves smooth style transitions through latent embedding interpolation

Outperforms existing methods in font generation quality

Enhances font design efficiency

Abstract

In this paper, we propose and end-to-end deep Chinese font generation system. This system can generate new style fonts by interpolation of latent style-related embeding variables that could achieve smooth transition between different style. Our method is simpler and more effective than other methods, which will help to improve the font design efficiency