3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information, including room layout, as well as furniture type, geometry, and placement. High-quality 3D indoor scenes are highly demanded while it requires expertise and is time-consuming to design high-quality 3D indoor scenes manually. Existing research only addresses partial problems: some works learn to generate room layout, and other works focus on generating detailed structure and geometry of individual furniture objects. However, these partial steps are related and should be addressed together for optimal synthesis. We propose SCENEHGN, a hierarchical graph network for 3D indoor scenes that takes into account the full hierarchy from the room level to the object level, then finally to the object part level. Therefore for the first time, our method is able to directly generate plausible 3D room content, including furniture objects with fine-grained geometry, and their layout. To address the challenge, we introduce functional regions as intermediate proxies between the room and object levels to make learning more manageable. To ensure plausibility, our graph-based representation incorporates both vertical edges connecting child nodes with parent nodes from different levels, and horizontal edges encoding relationships between nodes at the same level. Extensive experiments demonstrate that our method produces superior generation results, even when comparing results of partial steps with alternative methods that can only achieve these. We also demonstrate that our method is effective for various applications such as part-level room editing, room interpolation, and room generation by arbitrary room boundaries.

翻译：3D室内场景广泛应用于计算机图形学领域，涵盖从室内设计、游戏到虚拟现实和增强现实等多种场景。此类场景包含丰富的信息，包括房间布局、家具类型、几何结构及摆放位置。高质量3D室内场景需求旺盛，但人工设计不仅需要专业知识，且耗时耗力。现有研究仅解决部分问题：部分工作学习生成房间布局，另一些工作则专注于生成单个家具物体的详细结构与几何。然而，这些分步骤任务相互关联，应联合处理以实现最优合成。我们提出SCENEHGN——一种面向3D室内场景的分层图网络，该网络完整考虑了从房间层级到物体层级、最终到物体部件层级的全层次结构。因此，本方法首次能够直接生成合理的3D房间内容，包括具有细粒度几何的家具物体及其布局。为解决这一挑战，我们引入功能区域作为房间层级与物体层级之间的中间代理，使学习过程更易管理。为确保合理性，我们的基于图的表示不仅包含连接不同层级父子节点的垂直边，还编码了同层级节点之间关系的水平边。大量实验表明，即便将本方法在分步骤任务中的结果与仅能完成这些任务的替代方法进行比较，我们的方法仍能产生更优的生成结果。我们还证明了该方法在部件级房间编辑、房间插值以及任意房间边界约束下的房间生成等多种应用中具有有效性。