Title
DualAST: Dual Style-Learning Networks for Artistic Style Transfer
Abstract
Artistic style transfer is an image editing task that aims at repainting everyday photographs with learned artistic styles. Existing methods learn styles from either a single style example or a collection of artworks. Accordingly, the stylization results are either inferior in visual quality or limited in style controllability. To tackle this problem, we propose a novel Dual Style-Learning Artisti...
Year
DOI
Venue
2021
10.1109/CVPR46437.2021.00093
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
Keywords
DocType
ISSN
Visualization,Computer vision,Image color analysis,Controllability,Pattern recognition,Task analysis
Conference
1063-6919
ISBN
Citations 
PageRank 
978-1-6654-4509-2
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Haibo Chen101.69
Lei Zhao263.82
Zhizhong Wang334.12
Huiming Zhang401.69
Zhiwen Zuo533.11
Ailin Li604.39
Wei Xing76416.54
Dongming Lu875.55