Light-Field Intrinsic Dataset

Light-field imaging has various advantages over the traditional 2D photography, such as depth estimation and occlusion detection, which can aid intrinsic decomposition. The extracted intrinsic layers enable multiple applications, such as light-field appearance editing. However, the current light-field intrinsic decomposition techniques primarily resort to qualitative comparisons, due to lack of ground-truth data. In this work, we address this problem by providing intrinsic dataset for real world and synthetic 4D and 3D (only horizontal parallax) light fields. The ground-truth intrinsic data comprises albedo, shading and specularity layers for all sub-aperture images. In case of synthetic data, we also provide ground-truth depth, normals, and further decomposition of shading into direct and indirect components. For real-world data acquisition, we make use of custom hardware and 3D printed objects, assuring precision during multi-pass capturing. We also perform, qualitative and quantitative, comparison of existing intrinsic decomposition algorithms for single image, video, and light field. To the best of our knowledge, this is the first such dataset for light fields, which is also applicable for single image, multi-view stereo, and video. c © 2018. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms. *indicates equal contribution