UrbanIR: Large-Scale Urban Scene Inverse Rendering from a Single Video
Authors: name: Zhi-Hao Lin, name: Bohan Liu, name: Yi-Ting Chen, name: David Forsyth, name: Jia-Bin Huang, name: Anand Bhattad, name: Shenlong Wang

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