Generative Layout Modeling using Constraint Graphs

Wamiq Para, Paul Guerrero, Tom Kelly, Leonidas Guibas, Peter Wonka

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

38 Scopus citations

Abstract

We propose a new generative model for layout generation. We generate layouts in three steps. First, we generate the layout elements as nodes in a layout graph. Second, we compute constraints between layout elements as edges in the layout graph. Third, we solve for the final layout using constrained optimization. For the first two steps, we build on recent transformer architectures. The layout optimization implements the constraints efficiently. We show three practical contributions compared to the state of the art: our work requires no user input, produces higher quality layouts, and enables many novel capabilities for conditional layout generation.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6670-6680
Number of pages11
ISBN (Electronic)9781665428125
DOIs
StatePublished - 2021
Event18th IEEE/CVF International Conference on Computer Vision, ICCV 2021 - Virtual, Online, Canada
Duration: Oct 11 2021Oct 17 2021

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
ISSN (Print)1550-5499

Conference

Conference18th IEEE/CVF International Conference on Computer Vision, ICCV 2021
Country/TerritoryCanada
CityVirtual, Online
Period10/11/2110/17/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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