mlsanityData to 14 Oct 2026

Prim2Room: Layout-Controllable Room Mesh Generation from Primitives

arXiv 2409.05380 ↗First posted 9 Sep 2024cs.CVcited by 2

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Abstract (arXiv)

We propose Prim2Room, a novel framework for controllable room mesh generation leveraging 2D layout conditions and 3D primitive retrieval to facilitate precise 3D layout specification. Diverging from existing methods that lack control and precision, our approach allows for detailed customization of room-scale environments. To overcome the limitations of previous methods, we introduce an adaptive viewpoint selection algorithm that allows the system to generate the furniture texture and geometry from more favorable views than predefined camera trajectories. Additionally, we employ non-rigid depth registration to ensure alignment between generated objects and their corresponding primitive while allowing for shape variations to maintain diversity. Our method not only enhances the accuracy and aesthetic appeal of generated 3D scenes but also provides a user-friendly platform for detailed room design.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 39 of its 51 references that are in the map. First posted on arXiv 9 Sep 2024.

Builds on

39 of 51 references.

References · 39

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27 more
  1. 2023ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillationcited by 1,219
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  5. 2023LayoutGPT: Compositional Visual Planning and Generation with Large Language Modelscited by 347
  6. 2023Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Modelscited by 245
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  11. 2018Scan2CAD: Learning CAD Model Alignment in RGB-D Scanscited by 142
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  13. 2021Unconstrained Scene Generation with Locally Conditioned Radiance Fieldscited by 130
  14. 2023Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fieldscited by 123
  15. 2023Compositional 3D Scene Generation using Locally Conditioned Diffusioncited by 101
  16. 2021Lepard: Learning partial point cloud matching in rigid and deformable scenescited by 85
  17. 2024BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapolationcited by 83
  18. 2023Ctrl-Room: Controllable Text-to-3D Room Meshes Generation with Layout Constraintscited by 60
  19. 2023ControlRoom3D: Room Generation using Semantic Proxy Roomscited by 56
  20. 2023RoomDreamer: Text-Driven 3D Indoor Scene Synthesis with Coherent Geometry and Texturecited by 53
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  22. 2023SceneTex: High-Quality Texture Synthesis for Indoor Scenes via Diffusion Priorscited by 43
  23. 2022Non-rigid Point Cloud Registration with Neural Deformation Pyramidcited by 42
  24. 2022IronDepth: Iterative Refinement of Single-View Depth using Surface Normal and its Uncertaintycited by 30
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  27. 2022SinGRAF: Learning a 3D Generative Radiance Field for a Single Scenecited by 11

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025Progressive Rendering Distillation: Adapting Stable Diffusion for Instant Text-to-Mesh Generation without 3D Datacited by 7
  2. 2025Top2Pano: Learning to Generate Indoor Panoramas from Top-Down Viewcited by 0