FreeScene: Mixed Graph Diffusion for 3D Scene Synthesis from Free Prompts
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Abstract (arXiv)
Controllability plays a crucial role in the practical applications of 3D indoor scene synthesis. Existing works either allow rough language-based control, that is convenient but lacks fine-grained scene customization, or employ graph based control, which offers better controllability but demands considerable knowledge for the cumbersome graph design process. To address these challenges, we present FreeScene, a user-friendly framework that enables both convenient and effective control for indoor scene synthesis.Specifically, FreeScene supports free-form user inputs including text description and/or reference images, allowing users to express versatile design intentions. The user inputs are adequately analyzed and integrated into a graph representation by a VLM-based Graph Designer. We then propose MG-DiT, a Mixed Graph Diffusion Transformer, which performs graph-aware denoising to enhance scene generation. Our MG-DiT not only excels at preserving graph structure but also offers broad applicability to various tasks, including, but not limited to, text-to-scene, graph-to-scene, and rearrangement, all within a single model. Extensive experiments demonstrate that FreeScene provides an efficient and user-friendly solution that unifies text-based and graph based scene synthesis, outperforming state-of-the-art methods in terms of both generation quality and controllability in a range of applications.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 45 of its 67 references that are in the map. First posted on arXiv 3 Jun 2025.
Builds on
45 of 67 references.
References · 45
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
- 2020Denoising Diffusion Probabilistic Modelscited by 21,076
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
- 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
- 2022Scalable Diffusion Models with Transformerscited by 6,054
- 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,101
- 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,333
- 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,719
- 2018Demystifying MMD GANscited by 1,293
- 2020A Generalization of Transformer Networks to Graphscited by 661
- 2022DiGress: Discrete Denoising diffusion for graph generationcited by 520
33 more
- 2016Semantic Scene Completion from a Single Depth Imagecited by 472
- 20203D-FRONT: 3D Furnished Rooms with layOuts and semaNTicscited by 380
- 20203D-FUTURE: 3D Furniture shape with TextUREcited by 311
- 2023Holodeck: Language Guided Generation of 3D Embodied AI Environmentscited by 268
- 2022The Role of ImageNet Classes in Fr'echet Inception Distancecited by 213
- 2021ATISS: Autoregressive Transformers for Indoor Scene Synthesiscited by 200
- 2023OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understandingcited by 184
- 2020Total3DUnderstanding: Joint Layout, Object Pose and Mesh Reconstruction for Indoor Scenes from a Single Imagecited by 172
- 2023DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesiscited by 166
- 2023LayoutDM: Discrete Diffusion Model for Controllable Layout Generationcited by 143
- 2024PhyScene: Physically Interactable 3D Scene Synthesis for Embodied AIcited by 125
- 2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Priorcited by 117
- 2018Fast and Flexible Indoor Scene Synthesis via Deep Convolutional Generative Modelscited by 106
- 2023MiDi: Mixed Graph and 3D Denoising Diffusion for Molecule Generationcited by 98
- 2018InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Datasetcited by 87
- 2021Graph-to-3D: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphscited by 84
- 2023AnyHome: Open-Vocabulary Generation of Structured and Textured 3D Homescited by 82
- 2016IM2CADcited by 78
- 2023LEGO-Net: Learning Regular Rearrangements of Objects in Roomscited by 76
- 2024EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusioncited by 67
- 2018Deep Generative Modeling for Scene Synthesis via Hybrid Representationscited by 63
- 2019SceneGraphNet: Neural Message Passing for 3D Indoor Scene Augmentationcited by 55
- 2018Cooperative Holistic Scene Understanding: Unifying 3D Object, Layout, and Camera Pose Estimationcited by 51
- 2024Graph Diffusion Transformers for Multi-Conditional Molecular Generationcited by 45
- 2023SceneHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation with Fine-Grained Geometrycited by 39
- 2015Text to 3D Scene Generation with Rich Lexical Groundingcited by 36
- 2024Mixed Diffusion for 3D Indoor Scene Synthesiscited by 32
- 2021Scene Synthesis via Uncertainty-Driven Attribute Synchronizationcited by 29
- 2021Indoor Scene Generation from a Collection of Semantic-Segmented Depth Imagescited by 27
- 2023Sparse Training of Discrete Diffusion Models for Graph Generationcited by 27
- 2017SceneSeer: 3D Scene Design with Natural Languagecited by 21
- 2024DeBaRA: Denoising-Based 3D Room Arrangement Generationcited by 20
- 2023Advances in Data-Driven Analysis and Synthesis of 3D Indoor Scenescited by 19
Built on by
Citing papers per year: 2025: 2; 2026: 6.
8 papers.
- 2025SemLayoutDiff: Semantic Layout Generation with Diffusion Model for Indoor Scene Synthesiscited by 6
- 2026SceneNAT: Masked Generative Modeling for Language-Guided Indoor Scene Synthesiscited by 2
- 2026Function2Scene: 3D Indoor Scene Layout from Functional Specificationscited by 1
- 2026Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generationcited by 1
- 2025FurniMAS: Language-Guided Furniture Decoration using Multi-Agent Systemcited by 0
- 2026VoxScene: Anchor-Conditioned Voxel Diffusion for Indoor Scene Arrangementcited by 0
- 2026Scene Retargeting: Learning Object Placement with Analogical Transfercited by 0
- 2026Frozen Scenes, Shifting Winners: Configuration Fragility in Text-to-3D Evaluationcited by 0
- 2026Frozen Scenes, Shifting Winners: Configuration Fragility in Text-to-3D Evaluation30 Sep 2026
- 2026Scene Retargeting: Learning Object Placement with Analogical Transfer29 Sep 2026
- 2026Global-Local Monte Carlo Tree Search in Vision-Language Models for Text-to-3D Indoor Scene Generation4 Jun 2026
- 2026Function2Scene: 3D Indoor Scene Layout from Functional Specifications29 May 2026
- 2026VoxScene: Anchor-Conditioned Voxel Diffusion for Indoor Scene Arrangement16 May 2026
- 2026SceneNAT: Masked Generative Modeling for Language-Guided Indoor Scene Synthesis12 Jan 2026
- 2025SemLayoutDiff: Semantic Layout Generation with Diffusion Model for Indoor Scene Synthesis26 Aug 2025
- 2025FurniMAS: Language-Guided Furniture Decoration using Multi-Agent System7 Jul 2025
Similar, not cited
Close in wording, no citation either way
- 2023CommonScenes: Generating Commonsense 3D Indoor Scenes with Scene Graph Diffusion
- 2025GeoSceneGraph: Geometric Scene Graph Diffusion Model for Text-guided 3D Indoor Scene Synthesis
- 2025MMGDreamer: Mixed-Modality Graph for Geometry-Controllable 3D Indoor Scene Generation
- 2024Planner3D: LLM-enhanced graph prior meets 3D indoor scene explicit regularization
- 2026Dependency-Aware Discrete Diffusion for Scene Graph Generation
- 2025ReSpace: Text-Driven Autoregressive 3D Indoor Scene Synthesis and Editing
- 20263D Scene Graph Prediction: Generating Hierarchical Models from Partially Observed Environments
- 2026FlowScene: Style-Consistent Indoor Scene Generation with Multimodal Graph Rectified Flow