A simple model for intrinsic image decomposition with depth cues

We present a model for intrinsic decomposition of RGB-D images. Our approach analyzes a single RGB-D image and estimates albedo and shading fields that explain the input. To disambiguate the problem, our model esti-mates a number of components that jointly account for the reconstructed shading. By decomposing the shading field, we can build in assumptions about image formation that help distinguish reflectance variation from shading. These assumptions are expressed as simple nonlocal regularizers. We evaluate the model on real-world images and on a chal-lenging synthetic dataset. The experimental results demon-strate that the presented approach outperforms prior mod-els for intrinsic decomposition of RGB-D images. 1