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 scenes are selected to emphasize a diverse set of material properties challenging for existing algorithms. We provide around 1.4 million images of 107 different scenes acquired from 100 viewing directions under 14 lighting conditions. We expect our dataset will be useful for evaluation and training of 3D reconstruction algorithms and for related tasks. The dataset is available at skoltech3d.appliedai.tech.

翻译：我们提出了一种用于多视角三维表面重建的新型多传感器数据集。该数据集包含来自不同分辨率及模态传感器的已配准RGB与深度数据，涵盖智能手机、Intel RealSense、Microsoft Kinect、工业相机及结构光扫描仪。场景选取侧重于具有挑战性的多样化材质属性，以测试现有算法的鲁棒性。我们提供了约140万张图像，这些图像来自107个不同场景，分别从100个视角方向及14种光照条件下采集。预计该数据集将适用于三维重建算法的评估与训练，以及相关研究任务。数据集可通过skoltech3d.appliedai.tech获取。