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

DeRenderNet: Intrinsic Image Decomposition of Urban Scenes with Shape-(In)dependent Shading Rendering