Self-Stylized Neural Painter

Qian Wang, Cai Guo, Hong Ning Dai, Ping Li

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

2 Citations (Scopus)


This work introduces Self-Stylized Neural Painter (SSNP) creating stylized artworks in a stroke-by-stroke manner. SSNP consists of digit artist, canvas, style-stroke generator (SSG). By using SSG to generate style strokes, SSNP creates different styles paintings based on the given images. We design SSG as a three-player game based on a generative adversarial network to produce pure-color strokes that are crucial for mimicking the physical strokes. Furthermore, the digital artist adjusts parameters of strokes (shape, size, transparency, and color) to reconstruct as much detailed content of the reference image as possible to improve the fidelity.

Original languageEnglish
Title of host publicationProceedings - SIGGRAPH Asia 2021 Posters, SA 2021
EditorsShuzo John Shiota, Ayumi Kimura
PublisherAssociation for Computing Machinery (ACM)
Number of pages2
ISBN (Electronic)9781450386876
Publication statusPublished - 14 Dec 2021
EventSIGGRAPH Asia 2021 - Computer Graphics and Interactive Techniques Conference, Asia - Tokyo, Japan
Duration: 14 Dec 202117 Dec 2021

Publication series

NameProceedings - SIGGRAPH Asia


ConferenceSIGGRAPH Asia 2021 - Computer Graphics and Interactive Techniques Conference, Asia
Internet address

Scopus Subject Areas

  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction


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