Chinese Typography Transfer

Understand

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 without pre-trained used in other deep models.