We introduce OpenIllumination, a real-world dataset containing over 108K
images of 64 objects with diverse materials, captured under 72 camera views and
a large number of different illuminations. For each image in the dataset, we
provide accurate camera parameters, illumination ground truth, and foreground
segmentation masks. Our dataset enables the quantitative evaluation of most
inverse rendering and material decomposition methods for real objects. We
examine several state-of-the-art inverse rendering methods on our dataset and
compare their performances. The dataset and code can be found on the project
page: this https URL

OpenIllumination 是一个包含 108k 多个图像的真实世界数据集，其中包括 64 个对象，具有不同的材料，在 72 个摄像机视图和大量不同的光照条件下捕获。我们提供了数据集中每个图像的准确相机参数、光照真值和前景分割掩码。该数据集可以对大多数反渲染和材料分解方法进行定量评估，并对数据集上的几种先进的反渲染方法进行了比较。数据集和代码可以在项目页面上找到：this https URL