  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.
