Exploiting 3D Variational Autoencoders for Interactive Vehicle Design

S. SAHA, L.L. MINKU, X. YAO, B. SENDHOFF, S. MENZEL

Research output: Book Chapters | Papers in Conference ProceedingsConference paper (refereed)Researchpeer-review

1 Citation (Scopus)

Abstract

In automotive digital development, 3D prototype creation is a team effort of designers and engineers, each contributing with ideas and technical evaluations through means of computer simulations. To support the team in the 3D design ideation and exploration task, we propose an interactive design system for assisted design explorations and faster performance estimations. We utilize the advantage of deep learning-based autoencoders to create a low-dimensional latent manifold of 3D designs, which is utilized within an interactive user interface to guide and strengthen the decision-making process. © The Author(s), 2022.
Original languageEnglish
Title of host publicationProceedings of the Design Society
PublisherCambridge University Press
Pages1747-1756
Number of pages10
Volume2
DOIs
Publication statusPublished - May 2022
Externally publishedYes

Bibliographical note

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement number 766186 (ECOLE).

Keywords

  • 3D modelling
  • collaborative design
  • data-driven design

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