CVGRNov 26, 2020

Generative Layout Modeling using Constraint Graphs

arXiv:2011.13417v195 citations
AI Analysis

This work addresses the problem of automated, high-quality layout generation for designers and potentially other applications requiring structured visual arrangements, representing an incremental improvement over existing methods.

This paper introduces a generative model for layout generation that operates in three steps: generating layout elements, computing constraints between them, and solving for the final layout using constrained optimization. The model requires no user input, produces higher quality layouts, and enables novel conditional layout generation capabilities.

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.

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