ML Anthology

Neural Contours: Learning to Draw Lines from 3D Shapes

Difan Liu, Mohamed Nabail, Aaron Hertzmann, Evangelos Kalogerakis
CVPR 2020
doi:10.1109/CVPR42600.2020.00547 /cvpr/2020/liu2020cvpr-neural/

Abstract

This paper introduces a method for learning to generate line drawings from 3D models. Our architecture incorporates a differentiable module operating on geometric features of the 3D model, and an image-based module operating on view-based shape representations. At test time, geometric and view-based reasoning are combined with the help of a neural module to create a line drawing. The model is trained on a large number of crowdsourced comparisons of line drawings. Experiments demonstrate that our method achieves significant improvements in line drawing over the state-of-the-art when evaluated on standard benchmarks, resulting in drawings that are comparable to those produced by experienced human artists.

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Cite

Text

Liu et al. "Neural Contours: Learning to Draw Lines from 3D Shapes." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020. doi:10.1109/CVPR42600.2020.00547

Markdown

[Liu et al. "Neural Contours: Learning to Draw Lines from 3D Shapes." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020.](https://mlanthology.org/cvpr/2020/liu2020cvpr-neural/) doi:10.1109/CVPR42600.2020.00547

BibTeX

@inproceedings{liu2020cvpr-neural,
  title     = {{Neural Contours: Learning to Draw Lines from 3D Shapes}},
  author    = {Liu, Difan and Nabail, Mohamed and Hertzmann, Aaron and Kalogerakis, Evangelos},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2020},
  doi       = {10.1109/CVPR42600.2020.00547},
  url       = {https://mlanthology.org/cvpr/2020/liu2020cvpr-neural/}
}