用2D布局和3D模型库生成可控的高精度房间网格，支持精细设计。
Prim2Room: Layout-Controllable Room Mesh Generation from Primitives
- 基于2D布局与3D原型检索，实现房间结构精准控制。
- 自适应视角选择提升家具纹理与几何生成质量。
- 适合需要精细3D场景设计的用户，如室内设计、游戏开发。
我们提出Prim2Room，一种利用2D布局条件和3D原型检索进行可控房间网格生成的新框架，以实现精确的3D布局指定。与现有方法缺乏控制力和精度不同，该方法支持对房间尺度环境的详细定制。为克服以往方法的局限性，我们引入自适应视角选择算法，使系统能从比预设相机轨迹更优的视角生成家具的纹理与几何结构。此外，采用非刚性深度配准确保生成物体与其对应原型之间的对齐，同时允许形状变化以保持多样性。本方法不仅提升了生成3D场景的准确性和美观度，还提供了一个友好的用户平台，支持细致的房间设计。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。