Physical Relation Reasoning for 3-D Object Detection

3-D object detection is an important problem in many intelligent system applications. Based on powerful spatial information provided by point clouds, existing methods focus primarily on the intrinsic geometric properties of objects while neglecting the physical relationships and interactions among the objects. This may lead to physically unreasonable predictions, such as floating objects or object volume overlaps. In this paper, we propose a novel 3-D object detection method from the perspective of physical relation reasoning. Specifically, we introduce two aspects of physical relations, including stability and volume exclusion. In addition, we introduce room layouts to assist in 3-D object detection and formulate two physical constraints on the basic of volume exclusion and stability to ensure that all objects conform to real-world physics constraints. We validate our proposed model on ScanNetV2 and SUN RGB-D datasets, and the results demonstrate the effectiveness.