Computational Visual Media Journal (Special issue of CVM2021)
dualFace: Two-Stage Drawing Guidance for Freehand Portrait Sketching
Zhengyu Huang*, Yichen Peng*, Tomohiro Hibino*, Chunqi Zhao**,
Haoran Xie*, Tsukasa Fukusato**,
Kazunori Miyata*
(JAIST*, University of Tokyo**)
[arXiv][PDF]
[Code][Youtube]
[Talk]
Abstract
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In this paper, we propose dualFace, a portrait drawing interface to assist users with different levels of drawing skills to complete recognizable and authentic face sketches.
dualFace consists of two-stage drawing assistance to provide global and local visual guidance: global guidance, which helps users draw contour lines of portraits (i.e., geometric structure), and local guidance, which helps users draws details of facial parts (which conform to user-drawn contour lines), inspired by traditional artist workflows in portrait drawing.
In the stage of global guidance, the user draws several contour lines, and dualFace then searches several relevant images from an internal database and displays the suggested face contour lines over the background of the canvas. In the stage of local guidance, we synthesize detailed portrait images with a deep generative model from user-drawn contour lines, but use the synthesized results as detailed drawing guidance.
We conducted a user study to verify the effectiveness of dualFace, and we confirmed that dualFace significantly helps achieve a detailed portrait sketch.
Video
dualFace: Global Guidance
dualFace: Local Guidance
Publication
Zhengyu Huang, Yichen Peng, Tomohiro Hibino, Chunqi Zhao, Haoran Xie, Tsukasa Fukusato, Kazunori Miyata. dualFace: Two-Stage Drawing Guidance for Freehand Portrait Sketching. Journal of Computational Visual Media, 2021.Acknowledgements
We thank the reviewers for their valuable comments. We also thank Toby Chong for his involvement in idea discussion. This work was supported by Grant from Tateishi Science and Technology Foundation, JSPS KAKENHI grant JP20K19845 and JP19K20316, Japan.
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