We present a new multi-sensor dataset for multi-view 3D surface reconstruction. It includes registered RGB and depth data from sensors of different resolutions and modalities: smartphones, Intel RealSense, Microsoft Kinect, industrial cameras, and structured-light scanner. The data for each scene is obtained under a large number of lighting conditions, and the scenes are selected to emphasize a diverse set of material properties challenging for existing algorithms. Overall, we provide around 1.4 million images of 107 different scenes acquired at 14 lighting conditions from 100 viewing directions. We expect our dataset will be useful for evaluation and training of 3D reconstruction algorithms of different types and for other related tasks.

翻译：我们提出了一个新的多传感器数据集，用于多视角三维表面重建。该数据集包含来自不同分辨率和模态传感器的配准RGB与深度数据：智能手机、英特尔实感（Intel RealSense）、微软Kinect、工业相机和结构光扫描仪。每个场景的数据均在大量光照条件下获取，场景选择着重强调对现有算法具有挑战性的多样化材质属性。总体而言，我们提供了来自107个不同场景的约140万张图像，这些图像在14种光照条件下从100个视角方向采集。我们期望该数据集将有助于不同类型三维重建算法的评估与训练，以及其他相关任务。