mlsanityData to 14 Oct 2026

Lay-Your-Scene: Natural Scene Layout Generation with Diffusion Transformers

arXiv 2505.04718 ↗First posted 7 May 2025cs.CV cs.LGcited by 7

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

We present Lay-Your-Scene (shorthand LayouSyn), a novel text-to-layout generation pipeline for natural scenes. Prior scene layout generation methods are either closed-vocabulary or use proprietary large language models for open-vocabulary generation, limiting their modeling capabilities and broader applicability in controllable image generation. In this work, we propose to use lightweight open-source language models to obtain scene elements from text prompts and a novel aspect-aware diffusion Transformer architecture trained in an open-vocabulary manner for conditional layout generation. Extensive experiments demonstrate that LayouSyn outperforms existing methods and achieves state-of-the-art performance on challenging spatial and numerical reasoning benchmarks. Additionally, we present two applications of LayouSyn. First, we show that coarse initialization from large language models can be seamlessly combined with our method to achieve better results. Second, we present a pipeline for adding objects to images, demonstrating the potential of LayouSyn in image editing applications.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 47 of its 56 references that are in the map. First posted on arXiv 7 May 2025.

Builds on

47 of 56 references.

Closest ancestors · 15

Same direction, newest first

  1. 2024Make It Count: Text-to-Image Generation with an Accurate Number of Objects14 Jun
  2. 2024InstanceDiffusion: Instance-level Control for Image Generation5 Feb
  3. 2023Ranni: Taming Text-to-Image Diffusion for Accurate Instruction Following28 Nov
  4. 2023LLM Blueprint: Enabling Text-to-Image Generation with Complex and Detailed Prompts16 Oct
  5. 2023BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusion20 Jul
  6. 2023RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths29 May
  7. 2023LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Models23 May
  8. 2023LayoutDM: Transformer-based Diffusion Model for Layout Generation4 May
  9. 2023LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Models21 Mar
  10. 2023LayoutDM: Discrete Diffusion Model for Controllable Layout Generation14 Mar
  11. 2023Adding Conditional Control to Text-to-Image Diffusion Models10 Feb
  12. 2023GLIGEN: Open-Set Grounded Text-to-Image Generation17 Jan
3 more
  1. 2022DiffusionDet: Diffusion Model for Object Detection17 Nov
  2. 2022DiffEdit: Diffusion-based semantic image editing with mask guidance20 Oct
  3. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models20 Dec

Other references · 32

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2014Microsoft COCO: Common Objects in Contextcited by 17,608
  5. 2022Training language models to follow instructions with human feedbackcited by 15,971
  6. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  7. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  8. 2022Scalable Diffusion Models with Transformerscited by 6,054
  9. 2022Classifier-Free Diffusion Guidancecited by 5,847
  10. 2021Zero-Shot Text-to-Image Generationcited by 4,288
  11. 2024Scaling Rectified Flow Transformers for High-Resolution Image Synthesiscited by 4,181
  12. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,761
20 more
  1. 2023Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detectioncited by 3,332
  2. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,333
  3. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,430
  4. 2023Kosmos-2: Grounding Multimodal Large Language Models to the Worldcited by 1,089
  5. 2024WorldSimBench: Towards Video Generation Models as World Simulatorscited by 881
  6. 2023PixArt-α: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesiscited by 864
  7. 2021Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Modelscited by 463
  8. 2023LayoutGPT: Compositional Visual Planning and Generation with Large Language Modelscited by 347
  9. 2023On the Importance of Noise Scheduling for Diffusion Modelscited by 194
  10. 2022ReCo: Region-Controlled Text-to-Image Generationcited by 179
  11. 2019LayoutGAN: Generating Graphic Layouts with Wireframe Discriminatorscited by 131
  12. 2020LayoutTransformer: Layout Generation and Completion with Self-attentioncited by 123
  13. 2019LayoutVAE: Stochastic Scene Layout Generation From a Label Setcited by 119
  14. 2023DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generationcited by 110
  15. 2022A Generalist Framework for Panoptic Segmentation of Images and Videoscited by 99
  16. 2021Variational Transformer Networks for Layout Generationcited by 88
  17. 2021BLT: Bidirectional Layout Transformer for Controllable Layout Generationcited by 69
  18. 2022LayoutFormer++: Conditional Graphic Layout Generation via Constraint Serialization and Decoding Space Restrictioncited by 43
  19. 2023Dolfin: Diffusion Layout Transformers without Autoencodercited by 23
  20. 2024Bayesian Diffusion Models for 3D Shape Reconstructioncited by 19

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 5; 2026: 2.

7 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2025Laytrol: Preserving Pretrained Knowledge in Layout Control for Multimodal Diffusion Transformers
  2. 2025A Two-Stage System for Layout-Controlled Image Generation using Large Language Models and Diffusion Models
  3. 2024SLayR: Scene Layout Generation with Rectified Flow
  4. 2023LAW-Diffusion: Complex Scene Generation by Diffusion with Layouts
  5. 2023Language-driven Scene Synthesis using Multi-conditional Diffusion Model
  6. 2024Training-free Composite Scene Generation for Layout-to-Image Synthesis
  7. 2025Layout2Scene: 3D Semantic Layout Guided Scene Generation via Geometry and Appearance Diffusion Priors
  8. 2023LayoutLLM-T2I: Eliciting Layout Guidance from LLM for Text-to-Image Generation