论文标题
在室内场景中的自动化家具拆除的布局意识
Layout Aware Inpainting for Automated Furniture Removal in Indoor Scenes
论文作者
论文摘要
我们解决了从房间的广角照片中检测和擦除家具的问题。室内场景的大型区域通常会导致涂层面膜内背景元素的几何不一致。为了解决这个问题，我们利用感知信息（例如实例分段和房间布局）来生成几何始终如一的房间的空白版本。我们共享重要的细节，以使该系统可行，例如每个平面内置，自动修正和纹理改进。我们提供详细的消融以及定性的例子，证明我们的设计选择是合理的。我们通过从房间中取出真实家具并使用虚拟家具重新装修来展示系统的应用。
We address the problem of detecting and erasing furniture from a wide angle photograph of a room. Inpainting large regions of an indoor scene often results in geometric inconsistencies of background elements within the inpaint mask. To address this problem, we utilize perceptual information (e.g. instance segmentation, and room layout) to produce a geometrically consistent empty version of a room. We share important details to make this system viable, such as per-plane inpainting, automatic rectification, and texture refinement. We provide detailed ablation along with qualitative examples, justifying our design choices. We show an application of our system by removing real furniture from a room and redecorating it with virtual furniture.
