PPI-NET: End-to-End Parametric Primitive Inference
Liang Wang Xiaogang Wang
In engineering applications, line, circle, arc, and point are collectively
referred to as primitives, and they play a crucial role in path planning,
simulation analysis, and manufacturing. When designing CAD models, engineers
typically start by sketching the model's orthographic view on paper or a
whiteboard and then translate the design intent into a CAD program. Although
this design method is powerful, it often involves challenging and repetitive
tasks, requiring engineers to perform numerous similar operations in each
design. To address this conversion process, we propose an efficient and
accurate end-to-end method that avoids the inefficiency and error accumulation
issues associated with using auto-regressive models to infer parametric
primitives from hand-drawn sketch images. Since our model samples match the
representation format of standard CAD software, they can be imported into CAD
software for solving, editing, and applied to downstream design tasks.