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We show how to build a model that allows realistic, free-viewpoint renderingsof a scene under novel lighting conditions from video. Our method -- UrbanIR:Urban Scene Inverse Rendering -- computes an inverse graphics representationfrom the video. UrbanIR jointly infers shape, albedo, visibility, and sun andsky illumination from a single video of unbounded outdoor scenes with unknownlighting. UrbanIR uses videos from cameras mounted on cars (in contrast to manyviews of the same points in typical NeRF-style estimation). As a result,standard methods produce poor geometry estimates (for example, roofs), andthere are numerous ''floaters''. Errors in inverse graphics inference canresult in strong rendering artifacts. UrbanIR uses novel losses to controlthese and other sources of error. UrbanIR uses a novel loss to make very goodestimates of shadow volumes in the original scene. The resultingrepresentations facilitate controllable editing, delivering photorealisticfree-viewpoint renderings of relit scenes and inserted objects. Qualitativeevaluation demonstrates strong improvements over the state-of-the-art.

UrbanIR: Large-Scale Urban Scene Inverse Rendering from a Single Video