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Diffusion-Based Document Layout Generation

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Document Analysis and Recognition - ICDAR 2023 (ICDAR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14187))

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Abstract

We develop a diffusion-based approach for various document layout sequence generation. Layout sequences specify the contents of a document design in an explicit format. Our novel diffusion-based approach works in the sequence domain rather than the image domain in order to permit more complex and realistic layouts. We also introduce a new metric, Document Earth Mover’s Distance (Doc-EMD). By considering similarity between heterogeneous categories document designs, we handle the shortcomings of prior document metrics that only evaluate the same category of layouts. Our empirical analysis shows that our diffusion-based approach is comparable to or outperforming other previous methods for layout generation across various document datasets. Moreover, our metric is capable of differentiating documents better than previous metrics for specific cases.

L. He—Work done while a research intern at Microsoft Cloud and AI.

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Authors and Affiliations

  1. Purdue University, West Lafayette, IN, 47906, USA

    Liu He

  2. Microsoft Cloud and AI, Bellevue, WA, 98004, USA

    Yijuan Lu, John Corring, Dinei Florencio & Cha Zhang

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  1. Liu He
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  2. Yijuan Lu
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  3. John Corring
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  4. Dinei Florencio
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  5. Cha Zhang
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Correspondence to Liu He , Yijuan Lu or John Corring .

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Editors and Affiliations

  1. TU Dortmund University, Dortmund, Germany

    Gernot A. Fink

  2. Adobe, College Park, MN, USA

    Rajiv Jain

  3. Osaka Metropolitan University, Osaka, Japan

    Koichi Kise

  4. Rochester Institute of Technology, Rochester, NY, USA

    Richard Zanibbi

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He, L., Lu, Y., Corring, J., Florencio, D., Zhang, C. (2023). Diffusion-Based Document Layout Generation. In: Fink, G.A., Jain, R., Kise, K., Zanibbi, R. (eds) Document Analysis and Recognition - ICDAR 2023. ICDAR 2023. Lecture Notes in Computer Science, vol 14187. Springer, Cham. https://doi.org/10.1007/978-3-031-41676-7_21

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  • DOI: https://doi.org/10.1007/978-3-031-41676-7_21

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