Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes

Kotovenko, Dmytro; Wright, Matthias; Heimbrecht, Arthur and Ommer, Björn (2021): Rethinking Style Transfer: From Pixels to Parameterized Brushstrokes. 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, 20-25 June 2021. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), New York: IEEE. pp. 12191-12200

Abstract

There have been many successful implementations of neural style transfer in recent years. In most of these works, the stylization process is confined to the pixel domain. How- ever, we argue that this representation is unnatural because paintings usually consist of brushstrokes rather than pixels. We propose a method to stylize images by optimizing parameterized brushstrokes instead of pixels and further introduce a simple differentiable rendering mechanism. Our approach significantly improves visual quality and enables additional control over the stylization process such as controlling the flow of brushstrokes through user input. We provide qualitative and quantitative evaluations that show the efficacy of the proposed parameterized representation.

• Item Type: Conference or Workshop Item (Paper)
• Faculties: History and Art History > Department of Art History > Art History
• Subjects: 000 Computer science, information and general works > 004 Data processing computer science; 700 Arts and recreation > 700 Arts
• Place of Publication: New York
• Language: English