LGCVGRApr 19, 2021

Engineering Sketch Generation for Computer-Aided Design

arXiv:2104.09621v179 citations
Originality Incremental advance
AI Analysis

This work addresses the need for automated sketch generation in computer-aided design, which is incremental as it builds on existing methods for engineering sketch synthesis.

The paper tackled the problem of learning-based engineering sketch generation for parametric CAD by proposing two generative models, CurveGen and TurtleGen, which produce more realistic sketches compared to the state-of-the-art, as validated by human perceptual evaluation.

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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