Face Sketch Synthesis from Coarse to Fine

Abstract

Synthesizing fine face sketches from photos is a valuable yet challenging problem in digital entertainment. Face sketches synthesized by conventional methods usually exhibit coarse structures of faces, whereas fine details are lost especially on some critical facial components. In this paper, by imitating the coarse-to-fine drawing process of artists, we propose a novel face sketch synthesis framework consisting of a coarse stage and a fine stage. In the coarse stage, a mapping relationship between face photos and sketches is learned via the convolutional neural network. It ensures that the synthesized sketches keep coarse structures of faces. Given the test photo and the coarse synthesized sketch, a probabilistic graphic model is designed to synthesize the delicate face sketch which has fine and critical details. Experimental results on public face sketch databases illustrate that our proposed framework outperforms the state-of-the-art methods in both quantitive and visual comparisons.

Cite

Text

Zhang et al. "Face Sketch Synthesis from Coarse to Fine." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12224

Markdown

[Zhang et al. "Face Sketch Synthesis from Coarse to Fine." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/zhang2018aaai-face/) doi:10.1609/AAAI.V32I1.12224

BibTeX

@inproceedings{zhang2018aaai-face,
  title     = {{Face Sketch Synthesis from Coarse to Fine}},
  author    = {Zhang, Mingjin and Wang, Nannan and Li, Yunsong and Wang, Ruxin and Gao, Xinbo},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {7558-7565},
  doi       = {10.1609/AAAI.V32I1.12224},
  url       = {https://mlanthology.org/aaai/2018/zhang2018aaai-face/}
}