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.
BibTeX
@article{para2020generative,
title = {Generative Layout Modeling using Constraint Graphs},
author = {Wamiq Para and Paul Guerrero and Tom Kelly and Leonidas Guibas and Peter Wonka},
doi = {https://tinyurl.com/4nb59s9a},
year = {2021},
date = {2021-01-01},
journal = {Proceedings of the IEEE/CVF international conference on computer vision},
pages = {6690--6700},
}