Two-stage Content-Aware Layout Generation for Poster Designs

Shang Chai, Liansheng Zhuang, Fengying Yan, Zihan Zhou

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Automatic layout generation models can generate numerous design layouts in a few seconds, which significantly reduces the amount of repetitive work for designers. However, most of these models consider the layout generation task as arranging layout elements with different attributes on a blank canvas, thus struggle to handle the case when an image is used as the layout background. Additionally, existing layout generation models often fail to incorporate explicit aesthetic principles such as alignment and non-overlap, and neglect implicit aesthetic principles which are hard to model. To address these issues, this paper proposes a two-stage content-aware layout generation framework for poster layout generation. Our framework consists of an aesthetics-conditioned layout generation module and a layout ranking module. The diffusion model based layout generation module utilizes an aesthetics-guided layout denoising process to sample layout proposals that meet explicit aesthetic constraints. The Auto-Encoder based layout ranking module then measures the distance between those proposals and real designs to determine the layout that best meets implicit aesthetic principles. Quantitative and qualitative experiments demonstrate that our method outperforms state-of-the-art content-aware layout generation models.

Original languageEnglish (US)
Title of host publicationMM 2023 - Proceedings of the 31st ACM International Conference on Multimedia
PublisherAssociation for Computing Machinery, Inc
Number of pages9
ISBN (Electronic)9798400701085
StatePublished - Oct 26 2023
Event31st ACM International Conference on Multimedia, MM 2023 - Ottawa, Canada
Duration: Oct 29 2023Nov 3 2023

Publication series

NameMM 2023 - Proceedings of the 31st ACM International Conference on Multimedia


Conference31st ACM International Conference on Multimedia, MM 2023

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Graphics and Computer-Aided Design
  • Human-Computer Interaction
  • Software

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