MVRoom: Controllable 3D Indoor Scene Generation with Multi-View Diffusion Models
Fang, Shaoheng, Yu, Chaohui, Wang, Fan, Huang, Qixing
–arXiv.org Artificial Intelligence
W e introduce MVRoom, a controllable novel view synthesis (NVS) pipeline for 3D indoor scenes that uses multi-view diffusion conditioned on a coarse 3D layout. MV-Room employs a two-stage design in which the 3D layout is used throughout to enforce multi-view consistency. The first stage employs novel representations to effectively bridge the 3D layout and consistent image-based condition signals for multi-view generation. The second stage performs image-conditioned multi-view generation, incorporating a layout-aware epipolar attention mechanism to enhance multi-view consistency during the diffusion process. Additionally, we introduce an iterative framework that generates 3D scenes with varying numbers of objects and scene complexities by recursively performing multi-view generation (MVRoom), supporting text-to-scene generation. Experimental results demonstrate that our approach achieves high-fidelity and controllable 3D scene generation for NVS, outperforming state-of-the-art baseline methods both quantitatively and qualitatively.
arXiv.org Artificial Intelligence
Dec-5-2025
- Country:
- Asia > China
- Yunnan Province > Kunming (0.04)
- Europe > Italy
- North America > United States
- District of Columbia > Washington (0.05)
- Texas > Travis County
- Austin (0.04)
- Asia > China
- Genre:
- Research Report > New Finding (0.66)
- Technology: