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Neural Design Network: Graphic Layout Generation with Constraints

arXiv 1912.09421 ↗First posted 19 Dec 2019cs.CVcited by 83

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Abstract (arXiv)

Graphic design is essential for visual communication with layouts being fundamental to composing attractive designs. Layout generation differs from pixel-level image synthesis and is unique in terms of the requirement of mutual relations among the desired components. We propose a method for design layout generation that can satisfy user-specified constraints. The proposed neural design network (NDN) consists of three modules. The first module predicts a graph with complete relations from a graph with user-specified relations. The second module generates a layout from the predicted graph. Finally, the third module fine-tunes the predicted layout. Quantitative and qualitative experiments demonstrate that the generated layouts are visually similar to real design layouts. We also construct real designs based on predicted layouts for a better understanding of the visual quality. Finally, we demonstrate a practical application on layout recommendation.

Key facts. Cited by 83 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Dec 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 11; 2022: 8; 2023: 21; 2024: 23; 2025: 13; 2026: 7.

83 papers.

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  1. 2023LayoutDM: Discrete Diffusion Model for Controllable Layout Generationcited by 141
  2. 2021Screen2Words: Automatic Mobile UI Summarization with Multimodal Learningcited by 119
  3. 2021CanvasVAE: Learning to Generate Vector Graphic Documentscited by 93
  4. 2021Variational Transformer Networks for Layout Generationcited by 88
  5. 2021Constrained Graphic Layout Generation via Latent Optimizationcited by 83
  6. 2021BLT: Bidirectional Layout Transformer for Controllable Layout Generationcited by 69
  7. 2021SketchGen: Generating Constrained CAD Sketchescited by 68
  8. 2023PosterLayout: A New Benchmark and Approach for Content-aware Visual-Textual Presentation Layoutcited by 60
  9. 2022Composition-aware Graphic Layout GAN for Visual-textual Presentation Designscited by 59
  10. 2023LayoutDM: Transformer-based Diffusion Model for Layout Generationcited by 57
  11. 2021Engineering Sketch Generation for Computer-Aided Designcited by 49
  12. 2023LayoutPrompter: Awaken the Design Ability of Large Language Modelscited by 47
38 more
  1. 2022LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space Restrictioncited by 43
  2. 2023Unifying Layout Generation with a Decoupled Diffusion Modelcited by 41
  3. 2023LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Modelscited by 40
  4. 2024Graphic Design with Large Multimodal Modelcited by 38
  5. 2023Relation-Aware Diffusion Model for Controllable Poster Layout Generationcited by 36
  6. 2023Retrieval-Augmented Layout Transformer for Content-Aware Layout Generationcited by 34
  7. 2022Geometry Aligned Variational Transformer for Image-conditioned Layout Generationcited by 33
  8. 2023Towards Flexible Multi-modal Document Modelscited by 30
  9. 2024Towards Aligned Layout Generation via Diffusion Model with Aesthetic Constraintscited by 26
  10. 2023PLay: Parametrically Conditioned Layout Generation using Latent Diffusioncited by 24
  11. 2023Dolfin: Diffusion Layout Transformers without Autoencodercited by 23
  12. 2024Visual Text Generation in the Wildcited by 22
  13. 2024LayoutFlow: Flow Matching for Layout Generationcited by 21
  14. 2021Understanding the Role of Scene Graphs in Visual Question Answeringcited by 20
  15. 2023DLT: Conditioned layout generation with Joint Discrete-Continuous Diffusion Layout Transformercited by 20
  16. 2022Aesthetic Text Logo Synthesis via Content-aware Layout Inferringcited by 19
  17. 2024Desigen: A Pipeline for Controllable Design Template Generationcited by 19
  18. 2023LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Modelscited by 17
  19. 2022LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designercited by 15
  20. 2023A Parse-Then-Place Approach for Generating Graphic Layouts from Textual Descriptionscited by 15
  21. 2023UI Layout Generation with LLMs Guided by UI Grammarcited by 15
  22. 2025PosterO: Structuring Layout Trees to Enable Language Models in Generalized Content-Aware Layout Generationcited by 15
  23. 2024SciPostLayout: A Dataset for Layout Analysis and Layout Generation of Scientific Posterscited by 14
  24. 2023Unsupervised Domain Adaption with Pixel-level Discriminator for Image-aware Layout Generationcited by 13
  25. 2023Towards Diverse and Consistent Typography Generationcited by 11
  26. 2024From Elements to Design: A Layered Approach for Automatic Graphic Design Compositioncited by 11
  27. 2025BannerAgency: Advertising Banner Design with Multimodal LLM Agentscited by 11
  28. 2024LTSim: Layout Transportation-based Similarity Measure for Evaluating Layout Generationcited by 10
  29. 2021Creating User Interface Mock-ups from High-Level Text Descriptions with Deep-Learning Modelscited by 8
  30. 2023Diverse Multimedia Layout Generation with Multi Choice Learningcited by 8
  31. 2025AesthetiQ: Enhancing Graphic Layout Design via Aesthetic-Aware Preference Alignment of Multi-modal Large Language Modelscited by 8
  32. 2024Constrained Layout Generation with Factor Graphscited by 6
  33. 2024Graph4GUI: Graph Neural Networks for Representing Graphical User Interfacescited by 6
  34. 2025LayoutCoT: Unleashing the Deep Reasoning Potential of Large Language Models for Layout Generationcited by 6
  35. 2025SEGA: A Stepwise Evolution Paradigm for Content-Aware Layout Generation with Design Priorcited by 6
  36. 2021Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenescited by 5
  37. 2021The Layout Generation Algorithm of Graphic Design Based on Transformer-CVAEcited by 5
  38. 2023Text2Poster: Laying out Stylized Texts on Retrieved Imagescited by 5

50 most cited of 83 All 83 (JSON)