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 language | English (US) |
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Title of host publication | Proceedings - 2021 IEEE/CVF International Conference on Computer Vision, ICCV 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 6670-6680 |
Number of pages | 11 |
ISBN (Electronic) | 9781665428125 |
DOIs | |
State | Published - 2021 |
Event | 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021 - Virtual, Online, Canada Duration: Oct 11 2021 → Oct 17 2021 |
Publication series
Name | Proceedings of the IEEE International Conference on Computer Vision |
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ISSN (Print) | 1550-5499 |
Conference
Conference | 18th IEEE/CVF International Conference on Computer Vision, ICCV 2021 |
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Country/Territory | Canada |
City | Virtual, Online |
Period | 10/11/21 → 10/17/21 |
Bibliographical note
Publisher Copyright:© 2021 IEEE
ASJC Scopus subject areas
- Software
- Computer Vision and Pattern Recognition