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Title: Deep texture cartoonization via unsupervised appearance regularization
Author(s): Liu, Xueting 
Li, Chengze 
Author(s): Wu, H.
Li, Y.
Wu, W.
Issue Date: 2021
Publisher: Elsevier
Journal: Computers & Graphics 
Volume: 97
Start page: 99
End page: 107
Texture plays an important role in cartoon images to represent materials of objects and enrich visual attractiveness. However, manually crafting a cartoon texture is not easy, so amateurs usually directly use cartoon textures downloaded from the Internet. Unfortunately, Internet resources are quite limited and often patented, which restrict the users from generating visually pleasant and personalized cartoon textures. In this paper, we propose a deep learning based method to generate cartoon textures from natural textures. Different from the existing photo cartoonization methods that only aim to generate cartoonic images, the key to our method is to generate cartoon textures that are both cartoonic and regular. To achieve this goal, we propose a regularization module to generate a regular natural texture with similar appearance as the input, and a cartoonization module to cartoffonize the regularized natural texture into a regular cartoon texture. Our method successfully produces cartoonic and regular textures from various natural textures.
DOI: 10.1016/j.cag.2021.04.015
CIHE Affiliated Publication: Yes
Appears in Collections:CIS Publication

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