Abstract
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.
Abstract (translated)
3D室内场景在计算机图形学中广泛应用,涵盖了室内设计、游戏、虚拟现实和增强现实等领域。它们包含了丰富的信息,包括房间布局、家具类型、几何形状和位置。高质量的3D室内场景非常需求,但需要专业知识,手动设计高质量的3D室内场景需要花费大量时间和精力。现有的研究只解决了部分问题:一些工作学习生成房间布局,其他工作关注生成 individual furniture objects 的详细结构和几何形状。然而,这些部分步骤是相关的,应该一起解决以最佳合成。我们提出了SCENEHGN,一个3D室内场景的Hierarchical Graph Network,考虑了从房间到对象的所有层级,最终到对象部分层级。因此,我们的方法第一次能够直接生成可信赖的3D房间内容,包括精细几何形状的家具对象和他们的位置。为了应对挑战,我们引入了功能区域作为房间和对象层级之间的中间代理,以便更易于管理学习。为了确保可信度,我们的基于图的表示包括垂直Edges连接不同层级的子节点和父节点,以及水平Edges编码同一层级节点之间的关系。广泛的实验表明,我们的方法产生更好的生成结果,即使将这些步骤的结果与只能实现这些步骤的其他方法进行比较。我们还证明,我们的方法适用于各种应用,例如部分级别房间编辑、房间插值和通过任意房间边界生成房间。
URL
https://arxiv.org/abs/2302.10237
