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SceneSeer: 3D Scene Design with Natural Language

arXiv 1703.00050 ↗First posted 28 Feb 2017cs.GR cs.CL cs.HCcited by 20

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Abstract (arXiv)

Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark contrast to the easiness with which people can use language to describe real and imaginary environments. We present SceneSeer: an interactive text to 3D scene generation system that allows a user to design 3D scenes using natural language. A user provides input text from which we extract explicit constraints on the objects that should appear in the scene. Given these explicit constraints, the system then uses a spatial knowledge base learned from an existing database of 3D scenes and 3D object models to infer an arrangement of the objects forming a natural scene matching the input description. Using textual commands the user can then iteratively refine the created scene by adding, removing, replacing, and manipulating objects. We evaluate the quality of 3D scenes generated by SceneSeer in a perceptual evaluation experiment where we compare against manually designed scenes and simpler baselines for 3D scene generation. We demonstrate how the generated scenes can be iteratively refined through simple natural language commands.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Feb 2017.

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Citing papers per year: 2022: 3; 2023: 5; 2024: 5; 2025: 5; 2026: 2.

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  1. 2023Holodeck: Language Guided Generation of 3D Embodied AI Environmentscited by 257
  2. 2023DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesiscited by 159
  3. 2024SceneCraft: An LLM Agent for Synthesizing 3D Scene as Blender Codecited by 125
  4. 2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Priorcited by 110
  5. 2023AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homescited by 81
  6. 2022MIME: Human-Aware 3D Scene Generationcited by 57
  7. 20223DALL-E: Integrating Text-to-Image AI in 3D Design Workflowscited by 41
  8. 2024CityCraft: A Real Crafter for 3D City Generationcited by 25
  9. 2022Learning 3D Scene Priors with 2D Supervisioncited by 24
  10. 2023RoomDesigner: Encoding Anchor-latents for Style-consistent and Shape-compatible Indoor Scene Generationcited by 12
  11. 2024SceneGenAgent: Precise Industrial Scene Generation with Coding Agentcited by 12
  12. 2023Language-driven Scene Synthesis using Multi-conditional Diffusion Modelcited by 10
8 more
  1. 2025PlaceIt3D: Language-Guided Object Placement in Real 3D Scenescited by 8
  2. 2025FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Promptscited by 8
  3. 2025From Programs to Poses: Factored Real-World Scene Generation via Learned Program Librariescited by 6
  4. 2024S-INF: Towards Realistic Indoor Scene Synthesis via Scene Implicit Neural Fieldcited by 3
  5. 2025Computer-Aided Layout Generation for Building Design: A Reviewcited by 3
  6. 20253D-Generalist: Self-Improving Vision-Language-Action Models for Crafting 3D Worldscited by 3
  7. 2026HOG-Layout: Hierarchical 3D Scene Generation, Optimization and Editing via Vision-Language Modelscited by 1
  8. 2026SPHERE: Adaptive VR Indoor Scene Generation via LLM-Enhanced Spatial Preference Learning and Human-in-the-Loop RLcited by 0