This work introduces Self-Stylized Neural Painter (SSNP), a deep neural network that automatically creates stylized artworks in a stroke-by-stroke manner. Our 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 by human artists. Furthermore, the digital artist adjusts the parameters of strokes (shape, size, transparency, and color) to reconstruct as many detailed contents of the reference image as possible to improve the fidelity.

Bibtex

@inproceedings{10.1145/3476124.3488617,
author = {Wang, Qian and Guo, Cai and Dai, Hong-Ning and Li, Ping},
title = {Self-Stylized Neural Painter},
year = {2021},
isbn = {9781450386876},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3476124.3488617},
doi = {10.1145/3476124.3488617},
booktitle = {SIGGRAPH Asia 2021 Posters},
articleno = {9},
numpages = {2},
location = {Tokyo, Japan},
series = {SA '21 Posters}
}