mlsanityData to 14 Oct 2026

Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint

arXiv 2410.15391 ↗First posted 20 Oct 2024cs.CVcited by 21

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Abstract (arXiv)

We present Layout-Your-3D, a framework that allows controllable and compositional 3D generation from text prompts. Existing text-to-3D methods often struggle to generate assets with plausible object interactions or require tedious optimization processes. To address these challenges, our approach leverages 2D layouts as a blueprint to facilitate precise and plausible control over 3D generation. Starting with a 2D layout provided by a user or generated from a text description, we first create a coarse 3D scene using a carefully designed initialization process based on efficient reconstruction models. To enforce coherent global 3D layouts and enhance the quality of instance appearances, we propose a collision-aware layout optimization process followed by instance-wise refinement. Experimental results demonstrate that Layout-Your-3D yields more reasonable and visually appealing compositional 3D assets while significantly reducing the time required for each prompt. Additionally, Layout-Your-3D can be easily applicable to downstream tasks, such as 3D editing and object insertion. Our project page is available at:https://colezwhy.github.io/layoutyour3d/

Key facts. Cited by 21 papers in the map (data through 14 Oct 2026). Builds on 45 of its 51 references that are in the map. First posted on arXiv 20 Oct 2024.

Builds on

45 of 51 references.

References · 45

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2023Segment Anythingcited by 8,234
  4. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  5. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,503
  6. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  7. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
  8. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,489
  9. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,219
  10. 2023MVDream: Multi-view Diffusion for 3D Generationcited by 938
  11. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
  12. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
33 more
  1. 2023GLIGEN: Open-Set Grounded Text-to-Image Generationcited by 781
  2. 2024LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creationcited by 739
  3. 2023Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Modelscited by 702
  4. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 689
  5. 2023Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creationcited by 687
  6. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 645
  7. 2023SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Renderingcited by 616
  8. 2024GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generationcited by 301
  9. 2023Text-to-3D using Gaussian Splattingcited by 299
  10. 2023LucidDreamer: Towards High-Fidelity Text-to-3D Generation via Interval Score Matchingcited by 290
  11. 2024GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Imagecited by 286
  12. 2023BoxDiff: Text-to-Image Synthesis with Training-Free Box-Constrained Diffusioncited by 282
  13. 2023GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Modelscited by 255
  14. 2023LLM-grounded Diffusion: Enhancing Prompt Understanding of Text-to-Image Diffusion Models with Large Language Modelscited by 243
  15. 2023Diffusion-based Generation, Optimization, and Planning in 3D Scenescited by 239
  16. 2023RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3Dcited by 168
  17. 2023Text-to-3D with Classifier Score Distillationcited by 128
  18. 2024MIGC: Multi-Instance Generation Controller for Text-to-Image Synthesiscited by 124
  19. 2024GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splattingcited by 109
  20. 2023Compositional 3D Scene Generation using Locally Conditioned Diffusioncited by 101
  21. 2023GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphscited by 97
  22. 2021Self-Supervised Collision Handling via Generative 3D Garment Models for Virtual Try-Oncited by 81
  23. 2024DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Samplingcited by 72
  24. 2024ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidancecited by 59
  25. 2023CompoNeRF: Text-guided Multi-object Compositional NeRF with Editable 3D Scene Layoutcited by 57
  26. 2023SceneWiz3D: Towards Text-guided 3D Scene Compositioncited by 54
  27. 2024REPARO: Compositional 3D Assets Generation with Differentiable 3D Layout Alignmentcited by 45
  28. 2023Pyramid Diffusion for Fine 3D Large Scene Generationcited by 44
  29. 2023CG3D: Compositional Generation for Text-to-3D via Gaussian Splattingcited by 42
  30. 2024ScaleDreamer: Scalable Text-to-3D Synthesis with Asynchronous Score Distillationcited by 27
  31. 2024Large Point-to-Gaussian Model for Image-to-3D Generationcited by 10
  32. 2024Grounded Compositional and Diverse Text-to-3D with Pretrained Multi-View Diffusion Modelcited by 3
  33. 2024COMOGen: A Controllable Text-to-3D Multi-object Generation Frameworkcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 15; 2026: 5.

21 papers.

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  1. 2025Multimodal Spatial Reasoning in the Large Model Era: A Survey and Benchmarkscited by 33
  2. 20253D Scene Generation: A Surveycited by 24
  3. 2025PAT3D: Physics-Augmented Text-to-3D Scene Generationcited by 16
  4. 2024Graph Canvas for Controllable 3D Scene Generationcited by 11
  5. 2025D2GS: Depth-and-Density Guided Gaussian Splatting for Stable and Accurate Sparse-View Reconstructioncited by 11
  6. 2025Conditional Panoramic Image Generation via Masked Autoregressive Modelingcited by 9
  7. 2025GENA3D: Generative Amodal 3D Modeling by Bridging 2D Priors and 3D Coherencecited by 6
  8. 2025Flash Sculptor: Modular 3D Worlds from Objectscited by 5
  9. 2025FreeInsert: Disentangled Text-Guided Object Insertion in 3D Gaussian Scene without Spatial Priorscited by 5
  10. 2025CoCo4D: Comprehensive and Complex 4D Scene Generationcited by 4
  11. 2025A Self-Conditioned Representation Guided Diffusion Model for Realistic Text-to-LiDAR Scene Generationcited by 4
  12. 20263D-Layout-R1: Structured Reasoning for Language-Instructed Spatial Editingcited by 4
9 more
  1. 2025AnimateScene: Camera-controllable Animation in Any Scenecited by 3
  2. 2025TabletopGen: Tabletop Scene Generation and Interactive Simulation for Robotic Manipulationcited by 3
  3. 2026Pano3DComposer: Feed-Forward Compositional 3D Scene Generation from Single Panoramic Imagecited by 2
  4. 2025DreamScene: 3D Gaussian-based End-to-end Text-to-3D Scene Generationcited by 1
  5. 2026DM-CFO: A Diffusion Model for Compositional 3D Tooth Generation with Collision-Free Optimizationcited by 1
  6. 2026Perceive-then-Plan: Layout-as-Policy for Monocular 3D Scene Layout Estimationcited by 1
  7. 2025Causal Reasoning Elicits Controllable 3D Scene Generationcited by 0
  8. 2025Drag4D: Align Your Motion with Text-Driven 3D Scene Generationcited by 0
  9. 2026Inclusive Interactive Collisions for Multi-View Consistent Compositional 3D Generationcited by 0