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FilmSceneDesigner: Chaining Set Design for Procedural Film Scene Generation

arXiv 2511.19137 ↗First posted 24 Nov 2025cs.CVcited by 0

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Abstract (arXiv)

Film set design plays a pivotal role in cinematic storytelling and shaping the visual atmosphere. However, the traditional process depends on expert-driven manual modeling, which is labor-intensive and time-consuming. To address this issue, we introduce FilmSceneDesigner, an automated scene generation system that emulates professional film set design workflow. Given a natural language description, including scene type, historical period, and style, we design an agent-based chaining framework to generate structured parameters aligned with film set design workflow, guided by prompt strategies that ensure parameter accuracy and coherence. On the other hand, we propose a procedural generation pipeline which executes a series of dedicated functions with the structured parameters for floorplan and structure generation, material assignment, door and window placement, and object retrieval and layout, ultimately constructing a complete film scene from scratch. Moreover, to enhance cinematic realism and asset diversity, we construct SetDepot-Pro, a curated dataset of 6,862 film-specific 3D assets and 733 materials. Experimental results and human evaluations demonstrate that our system produces structurally sound scenes with strong cinematic fidelity, supporting downstream tasks such as virtual previs, construction drawing and mood board creation.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 20 of its 32 references that are in the map. First posted on arXiv 24 Nov 2025.

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20 of 32 references.

References · 20

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  3. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
  4. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,522
  5. 20203D-FRONT: 3D Furnished Rooms with layOuts and semaNTicscited by 375
  6. 20203D-FUTURE: 3D Furniture shape with TextUREcited by 306
  7. 2023Holodeck: Language Guided Generation of 3D Embodied AI Environmentscited by 257
  8. 2023SceneScape: Text-Driven Consistent Scene Generationcited by 160
  9. 2023DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesiscited by 159
  10. 2024GPT-4V(ision) is a Human-Aligned Evaluator for Text-to-3D Generationcited by 151
  11. 2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Priorcited by 110
  12. 2023GraphDreamer: Compositional 3D Scene Synthesis from Scene Graphscited by 96
8 more
  1. 2024I-Design: Personalized LLM Interior Designercited by 87
  2. 2023AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homescited by 81
  3. 2024DreamScene: 3D Gaussian-based Text-to-3D Scene Generation via Formation Pattern Samplingcited by 72
  4. 2024EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusioncited by 66
  5. 2023Ctrl-Room: Controllable Text-to-3D Room Meshes Generation with Layout Constraintscited by 59
  6. 2023CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph Diffusioncited by 54
  7. 2025FlairGPT: Repurposing LLMs for Interior Designscited by 22
  8. 2018Fast and Scalable Position-Based Layout Synthesiscited by 15

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