FontRNN: Generating Large-scale Chinese Fonts via Recurrent Neural Network

1 code implementation • Computer Graphics Forum 2019 • Shusen Tang, Zeqing Xia, Zhouhui Lian, Yingmin Tang, Jianguo Xiao

Despite the recent impressive development of deep neural networks, using deep learning based methods to generate large-scale Chinese fonts is still a rather challenging task due to the huge number of intricate Chinese glyphs, e. g., the official standard Chinese charset GB18030-2000 consists of 27, 533 Chinese characters.

Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning

3 code implementations • 11 Oct 2019 • Yue Gao, Yuan Guo, Zhouhui Lian, Yingmin Tang, Jianguo Xiao

Extensive experiments on both English and Chinese artistic glyph image datasets demonstrate the superiority of our model in generating high-quality stylized glyph images against other state-of-the-art methods.

Few-Shot Learning Image Generation

Boosting Scene Character Recognition by Learning Canonical Forms of Glyphs

1 code implementation • 12 Jul 2019 • Yizhi Wang, Zhouhui Lian, Yingmin Tang, Jianguo Xiao

In this paper, we propose a novel methodology for boosting scene character recognition by learning canonical forms of glyphs, based on the fact that characters appearing in scene images are all derived from their corresponding canonical forms.

A Common Framework for Interactive Texture Transfer

no code implementations • CVPR 2018 • Yifang Men, Zhouhui Lian, Yingmin Tang, Jianguo Xiao

In this paper, we present a general-purpose solution to interactive texture transfer problems that better preserves both local structure and visual richness.