Abstract
We present a pipeline for generating defurnished replicas of indoor spaces represented as textured meshes and corresponding multi-view panoramic images. To achieve this, we first segment and remove furniture from the mesh representation, extend planes, and fill holes, obtaining a simplified defurnished mesh (SDM). This SDM acts as an ``X-ray'' of the scene's underlying structure, guiding the defurnishing process. We extract Canny edges from depth and normal images rendered from the SDM. We then use these as a guide to remove the furniture from panorama images via ControlNet inpainting. This control signal ensures the availability of global geometric information that may be hidden from a particular panoramic view by the furniture being removed. The inpainted panoramas are used to texture the mesh. We show that our approach produces higher quality assets than methods that rely on neural radiance fields, which tend to produce blurry low-resolution images, or RGB-D inpainting, which is highly susceptible to hallucinations.
Abstract (translated)
我们提出了一种生成室内空间去家具化副本的流水线，这些室内空间以带纹理的网格和相应的多视角全景图像表示。为实现这一目标，我们首先从网格表示中分割并移除家具，扩展平面，并填充空洞，从而获得一个简化的无家具网格（SDM）。这个SDM充当场景底层结构的“X光片”，引导去家具化过程。我们从SDM渲染的深度和法线图像中提取Canny边缘。然后利用这些信息作为指导，通过ControlNet插值移除全景图中的家具。这一控制信号确保了全局几何信息的可用性，即便在特定全景视图中被移除的家具所遮挡的情况下也是如此。处理后的全景图用于为网格添加纹理。 我们展示了我们的方法相较于依赖神经辐射场的方法产生更高质量的资产，后者往往生成模糊且低分辨率的图像；同时也优于RGB-D插值方法，后者容易出现幻觉（即错误生成）。
URL
https://arxiv.org/abs/2506.05338
