  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.
