Engineering Sketch Generation for Computer-Aided Design
Karl D.D. Willis, Pradeep Kumar Jayaraman, Joseph G. Lambourne, Hang, Chu, Yewen Pu

TL;DR
This paper introduces two generative models, CurveGen and TurtleGen, for creating engineering sketches in CAD, improving realism and topology consideration without relying on sketch constraint solvers.
Contribution
The paper presents novel generative models for engineering sketch creation that enhance realism and explicitly incorporate topology, advancing CAD model synthesis.
Findings
Both models produce more realistic sketches than existing methods.
Models generate curve primitives without constraint solvers.
Perceptual evaluation confirms improved realism.
Abstract
Engineering sketches form the 2D basis of parametric Computer-Aided Design (CAD), the foremost modeling paradigm for manufactured objects. In this paper we tackle the problem of learning based engineering sketch generation as a first step towards synthesis and composition of parametric CAD models. We propose two generative models, CurveGen and TurtleGen, for engineering sketch generation. Both models generate curve primitives without the need for a sketch constraint solver and explicitly consider topology for downstream use with constraints and 3D CAD modeling operations. We find in our perceptual evaluation using human subjects that both CurveGen and TurtleGen produce more realistic engineering sketches when compared with the current state-of-the-art for engineering sketch generation.
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Taxonomy
Topics3D Shape Modeling and Analysis · Human Motion and Animation · Computer Graphics and Visualization Techniques
