  We address the dual problems of novel view synthesis and environment
reconstruction from hand-held RGBD sensors. Our contributions include 1)
modeling highly specular objects, 2) modeling inter-reflections and Fresnel
effects, and 3) enabling surface light field reconstruction with the same input
needed to reconstruct shape alone. In cases where scene surface has a strong
mirror-like material component, we generate highly detailed environment images,
revealing room composition, objects, people, buildings, and trees visible
through windows. Our approach yields state of the art view synthesis
techniques, operates on low dynamic range imagery, and is robust to geometric
and calibration errors.
