论文标题
神经轮廓：学习从3D形状绘制线条
Neural Contours: Learning to Draw Lines from 3D Shapes
论文作者
论文摘要
本文介绍了一种学习从3D模型生成线条图的方法。我们的体系结构结合了一个在3D模型的几何特征上运行的可区分模块，以及在基于视图的形状表示上运行的基于图像的模块。在测试时，将基于几何和基于视图的推理在神经模块的帮助下结合使用，以创建线图。该模型经过大量众包线图的比较。实验表明，我们的方法在对标准基准测试进行评估时，在最先进的线路上取得了显着改善，从而导致图纸与经验丰富的人类艺术家所产生的图纸相当。
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.
