A survey of stroke-based rendering
By Aaron Hertzmann. IEEE Computer Graphics and Applications, 2003
297 citations recorded by the source corpus.
Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/46261bc8d499d5a43ded2112df27980dcaf846d3
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Graphics and Computer-Aided Design
- Michael Gharbi
- Michal Lukác
- Tzu-Mao Li
- Jonathan Ragan-Kelley
- Aaron Hertzmann
- Yingtao Tian
- David R Ha
- Bing-Yu Chen
In Computer Vision and Pattern Recognition
- Michael Gharbi
- Michal Lukác
- Jonathan Ragan-Kelley
- Tzu-Mao Li
- Aaron Hertzmann
- Ming-Hsuan Yang
- Luc Van Gool
- Jitendra Malik
Citations in the corpus
- Differentiable vector graphics rasterization for editing and learning (2020, methodology): “This achieves initialization L 2 loss perceptual loss target by optimization results similar to what painterly rendering algorithms [Hertzmann 1998, 2003] do by employing heuristics, or more recently reinforcement learning [Ganin et al. 2018; Nakano 2019].”
- Why Do Line Drawings Work? A Realism Hypothesis (2020, methodology): “3D stylization algorithms that directly optimize for perceptual similarity may be useful in modeling other styles, for example, Hertzmann (2003), Nakano (2019), and Mellor et al. (2019).”