Publication | International Conference on Machine Learning 2022
SkexGen
Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
This Autodesk Research paper describes a new approach to generation of solid CAD models that enhances user control and enables efficient exploration of the design space.
Download publicationAbstract
SkexGen: Autoregressive Generation of CAD Construction Sequences with Disentangled Codebooks
Xiang Xu, Karl D.D. Willis, Joseph G. Lambourne, Chin-Yi Cheng, Pradeep Kumar Jayaraman, Yasutaka Furukawa
International Conference on Machine Learning 2022
We present SkexGen, a novel autoregressive generative model for computer-aided design (CAD) construction sequences containing sketch-and-extrude modeling operations. Our model utilizes distinct Transformer architectures to encode topological, geometric, and extrusion variations of construction sequences into disentangled codebooks. Autoregressive Transformer decoders generate CAD construction sequences sharing certain properties specified by the codebook vectors. Extensive experiments demonstrate that our disentangled codebook representation generates diverse and high-quality CAD models, enhances user control, and enables efficient exploration of the design space.
Associated Researchers
Chin-Yi Cheng
Autodesk Research
Yasutaka Furukawa
Simon Fraser University
Related Resources
2024
A hyperreduced reduced basis element method for reduced-order modeling of component-based nonlinear systemsThis method balances accuracy and computational speed through adaptive…
2020
Learning to Simulate and Design for Structural EngineeringThe structural design process for buildings is time consuming and…
2021
LSD-StructureNet: Modeling Levels of Structural Detail in 3D Part HierarchiesGenerative models for 3D shapes represented by hierarchies of parts…
2022
Assemble Them All: Physics-Based Planning for Generalizable Assembly by DisassemblyThis work proposes a novel method to efficiently plan physically…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us