  We propose DeRenderNet, a deep neural network to decompose the albedo and
latent lighting, and render shape-(in)dependent shadings, given a single image
of an outdoor urban scene, trained in a self-supervised manner. To achieve this
goal, we propose to use the albedo maps extracted from scenes in videogames as
direct supervision and pre-compute the normal and shadow prior maps based on
the depth maps provided as indirect supervision. Compared with state-of-the-art
intrinsic image decomposition methods, DeRenderNet produces shadow-free albedo
maps with clean details and an accurate prediction of shadows in the
shape-independent shading, which is shown to be effective in re-rendering and
improving the accuracy of high-level vision tasks for urban scenes.
