Hatching is a common method used by artists to accentuate the third dimension of a sketch, and to illuminate the scene. Our system SHAD3S attempts to compete with a human at hatching generic three-dimensional (3D) shapes, and also tries to assist her in a form exploration exercise. The novelty of our approach lies in the fact that we make no assumptions about the input other than that it represents a 3D shape, and yet, given a contextual information of illumination and texture, we synthesise an accurate hatch pattern over the sketch, without access to 3D or pseudo 3D. In the process, we contribute towards a) a cheap yet effective method to synthesise a sufficiently large high fidelity dataset, pertinent to task; b) creating a pipeline with conditional generative adversarial network (CGAN); and c) creating an interactive utility with GIMP, that is a tool for artists to engage with automated hatching or a form-exploration exercise. User evaluation of the tool suggests that the model performance does generalise satisfactorily over diverse input, both in terms of style as well as shape. A simple comparison of inception scores suggest that the generated distribution is as diverse as the ground truth.

中文翻译：

---

SHAD3S：素描、阴影和阴影的模型

影线是艺术家用来突出草图的第三维并照亮场景的常用方法。我们的系统 SHAD3S 尝试在孵化通用 3D (3D) 形状方面与人类竞争，并尝试协助她进行形式探索练习。我们方法的新颖之处在于，除了表示 3D 形状之外，我们对输入不做任何假设，然而，给定照明和纹理的上下文信息，我们在草图上合成了准确的填充图案，无需访问到 3D 或伪 3D。在此过程中，我们致力于 a) 一种廉价但有效的方法来合成与任务相关的足够大的高保真数据集；b) 使用条件生成对抗网络 (CGAN) 创建管道；c) 使用 GIMP 创建一个交互式实用程序，这是艺术家参与自动孵化或形式探索练习的工具。用户对该工具的评估表明，模型性能确实可以令人满意地概括各种输入，无论是样式还是形状。对初始分数的简单比较表明，生成的分布与基本事实一样多样化。