OpenSubstance: A High-Quality Measured Dataset of Multi-View and -Lighting Images and Shapes (Part 4)

We present OpenSubstance, a high-quality measured dataset with 2.4 million high-dynamic-range images of 187 objects with a wide variety in shape and appearance, captured under 270 camera views and 1,637 lighting conditions, including 1,620 one-light-at-a-time, 8 environment, 8 linear, and 1 full-on illumination. For each image, the corresponding lighting condition, camera parameters, and foreground segmentation mask are provided. High-precision 3D geometry is also acquired for rigid objects. It takes 1 hour on average to capture one object with our custom-built high-performance lightstage and a top-grade commercial 3D scanner. We perform comprehensive quantitative evaluation on state-of-the-art techniques across different tasks, including single- and multi-view photometric stereo, as well as relighting. The project is publicly available at https://opensubstance.github.io/This dataset includes part of raw images data.

我们提出了OpenSubstance数据集——这是一套高质量实测数据集，包含187种形状与外观差异显著的物体的240万张高动态范围图像，所有图像均在270个相机视角与1637种光照条件下采集得到，其中涵盖1620种单次单光源照明场景、8种环境光照场景、8种线性光照场景以及1种全亮照明场景。每张图像均附带对应的光照条件参数、相机参数与前景分割掩码。针对刚体物体，我们还采集了高精度三维几何数据。使用我们定制的高性能光照采集平台与顶级商用三维扫描仪，平均每采集一个物体需要耗时1小时。我们针对当前顶尖技术在多项任务中开展了全面的定量评估，涵盖单视图光度立体视觉、多视图光度立体视觉以及重光照任务。本项目已公开至https://opensubstance.github.io/，本数据集包含部分原始图像数据。