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: https://oppo-us-research.github.io/OpenIllumination.

翻译：我们提出OpenIllumination，一个包含64种不同材质物体、超过10.8万张图像的真实世界数据集，所有图像均在72个相机视角和大量不同光照条件下拍摄。数据集中每张图像均提供精确的相机参数、光照真值及前景分割掩码。该数据集能够对面向真实物体的主流逆渲染与材质分解方法进行定量评估。我们在该数据集上测试了多种最新逆渲染方法，并对比了其性能。数据集与代码可在项目主页获取：https://oppo-us-research.github.io/OpenIllumination。