论文标题
Layoutmp3D：MatterPort3D的布局注释
LayoutMP3D: Layout Annotation of Matterport3D
论文作者
论文摘要
从单个等方面的全景中推断3D布局的信息对于虚拟现实或机器人技术的众多应用至关重要（例如，场景的理解和导航）。为此，为360个布局估计的任务收集了几个数据集。为了促进在室内场景中自治系统的学习算法，我们考虑了Matterport3D数据集及其最初提供的深度地图地面真理，并进一步释放我们从MatterPort3D子集的布局地面真相的注释。由于MatterPort3D包含飞行时间（TOF）传感器的准确深度地面真相，因此我们的数据集既提供了布局和深度信息，从而有机会通过集成两个提示来探索环境。
Inferring the information of 3D layout from a single equirectangular panorama is crucial for numerous applications of virtual reality or robotics (e.g., scene understanding and navigation). To achieve this, several datasets are collected for the task of 360 layout estimation. To facilitate the learning algorithms for autonomous systems in indoor scenarios, we consider the Matterport3D dataset with their originally provided depth map ground truths and further release our annotations for layout ground truths from a subset of Matterport3D. As Matterport3D contains accurate depth ground truths from time-of-flight (ToF) sensors, our dataset provides both the layout and depth information, which enables the opportunity to explore the environment by integrating both cues.
