publication . Preprint . 2017

Chinese Typography Transfer

Chang, Jie; Gu, Yujun;
Open Access English
  • Published: 16 Jul 2017
In this paper, we propose a new network architecture for Chinese typography transformation based on deep learning. The architecture consists of two sub-networks: (1)a fully convolutional network(FCN) aiming at transferring specified typography style to another in condition of preserving structure information; (2)an adversarial network aiming at generating more realistic strokes in some details. Unlike models proposed before 2012 relying on the complex segmentation of Chinese components or strokes, our model treats every Chinese character as an inseparable image, so pre-processing or post-preprocessing are abandoned. Besides, our model adopts end-to-end training ...
free text keywords: Computer Science - Computer Vision and Pattern Recognition
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