While free-hand sketching has long served as an efficient representation to convey characteristics of an object, they are often subjective, deviating significantly from realistic representations. Moreover, sketches are not consistent for arbitrary viewpoints, making it hard to catch 3D shapes. We propose 3Dooole, generating descriptive and view-consistent sketch images given multi-view images of the target object. Our method is based on the idea that a set of 3D strokes can efficiently represent 3D structural information and render view-consistent 2D sketches. We express 2D sketches as a union of view-independent and view-dependent components. 3D cubic B ezier curves indicate view-independent 3D feature lines, while contours of superquadrics express a smooth outline of the volume of varying viewpoints. Our pipeline directly optimizes the parameters of 3D stroke primitives to minimize perceptual losses in a fully differentiable manner. The resulting sparse set of 3D strokes can be rendered as abstract sketches containing essential 3D characteristic shapes of various objects. We demonstrate that 3Doodle can faithfully express concepts of the original images compared with recent sketch generation approaches.

翻译：虽然手绘草图长期以来一直是传达物体特征的高效表示方式，但这类草图往往带有主观性，与真实表示存在显著偏差。此外，草图在不同视角下缺乏一致性，导致难以捕捉三维形状。我们提出3Doodle方法，通过目标物体的多视角图像生成具有描述性与视角一致性的草图图像。该方法基于以下核心理念：一组三维笔触能够高效表示三维结构信息，并渲染出视角一致的二维草图。我们将二维草图分解为视角无关与视角相关两部分：三维三次贝塞尔曲线表示视角无关的三维特征线，而超二次曲面轮廓则表达不同视角下体积的平滑边界。我们的流程直接优化三维笔触基元的参数，以完全可微的方式最小化感知损失。最终得到的稀疏三维笔触集合可渲染为包含各类物体关键三维特征形状的抽象草图。实验表明，与近期草图生成方法相比，3Doodle能更忠实地表达原始图像的语义概念。