Neural Contours: Learning to Draw Lines from 3D Shapes

• URL: http://arxiv.org/abs/2003.10333v3
• Date: Sun, 5 Apr 2020 03:22:55 GMT
• Title: Neural Contours: Learning to Draw Lines from 3D Shapes
• Authors: Difan Liu, Mohamed Nabail, Aaron Hertzmann, Evangelos Kalogerakis
• Abstract summary: 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.
• Score: 20.650770317411233
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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