Deep Style Transfer for Line Drawings

Authors

  • Xueting Liu Shenzhen University
  • Wenliang Wu Shenzhen University
  • Huisi Wu Shenzhen University
  • Zhenkun Wen Shenzhen University

Keywords:

Art/Music/Creativity

Abstract

Line drawings are frequently used to illustrate ideas and concepts in digital documents and presentations. To compose a line drawing, it is common for users to retrieve multiple line drawings from the Internet and combine them as one image. However, different line drawings may have different line styles and are visually inconsistent when put together. In order that the line drawings can have consistent looks, in this paper, we make the first attempt to perform style transfer for line drawings. The key of our design lies in the fact that centerline plays a very important role in preserving line topology and extracting style features. With this finding, we propose to formulate the style transfer problem as a centerline stylization problem and solve it via a novel style-guided image-to-image translation network. Results and statistics show that our method significantly outperforms the existing methods both visually and quantitatively.

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Published

2021-05-18

How to Cite

Liu, X., Wu, W., Wu, H., & Wen, Z. (2021). Deep Style Transfer for Line Drawings. Proceedings of the AAAI Conference on Artificial Intelligence, 35(1), 353-361. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/16111

Issue

Section

AAAI Technical Track on Application Domains