Constrained Graphic Layout Generation via Latent Optimization

• URL: http://arxiv.org/abs/2108.00871v1
• Date: Mon, 2 Aug 2021 13:04:11 GMT
• Title: Constrained Graphic Layout Generation via Latent Optimization
• Authors: Kotaro Kikuchi, Edgar Simo-Serra, Mayu Otani, Kota Yamaguchi
• Abstract summary: We generate graphic layouts that can flexibly incorporate design semantics, either specified implicitly or explicitly by a user. Our approach builds on a generative layout model based on a Transformer architecture, and formulates the layout generation as a constrained optimization problem. We show in the experiments that our approach is capable of generating realistic layouts in both constrained and unconstrained generation tasks with a single model.
• Score: 17.05026043385661
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: It is common in graphic design humans visually arrange various elements according to their design intent and semantics. For example, a title text almost always appears on top of other elements in a document. In this work, we generate graphic layouts that can flexibly incorporate such design semantics, either specified implicitly or explicitly by a user. We optimize using the latent space of an off-the-shelf layout generation model, allowing our approach to be complementary to and used with existing layout generation models. Our approach builds on a generative layout model based on a Transformer architecture, and formulates the layout generation as a constrained optimization problem where design constraints are used for element alignment, overlap avoidance, or any other user-specified relationship. We show in the experiments that our approach is capable of generating realistic layouts in both constrained and unconstrained generation tasks with a single model. The code is available at https://github.com/ktrk115/const_layout .

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