A Style-Based Generator Architecture for Generative Adversarial Networks

@article{Karras2018ASG,
  title={A Style-Based Generator Architecture for Generative Adversarial Networks},
  author={Tero Karras and Samuli Laine and Timo Aila},
  journal={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2018},
  pages={4396-4405}
}
  • Tero KarrasS. LaineTimo Aila
  • Published 12 December 2018
  • Computer Science
  • 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
We propose an alternative generator architecture for generative adversarial networks, borrowing from style transfer literature. [] Key Method To quantify interpolation quality and disentanglement, we propose two new, automated methods that are applicable to any generator architecture. Finally, we introduce a new, highly varied and high-quality dataset of human faces.
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