Neural Contours: Learning to Draw Lines from 3D Shapes
This addresses the challenge of automated line drawing creation for applications in computer graphics and design, representing a strong specific gain rather than a foundational advancement.
The paper tackles the problem of generating line drawings from 3D models by introducing a method that combines geometric and view-based reasoning with a neural module, achieving significant improvements over state-of-the-art methods on standard benchmarks and producing drawings comparable to those by experienced human artists.
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.