  Urban 3D modeling from satellite images requires accurate semantic
segmentation to delineate urban features, multiple view stereo for 3D
reconstruction of surface heights, and 3D model fitting to produce compact
models with accurate surface slopes. In this work, we present a cumulative
assessment metric that succinctly captures error contributions from each of
these components. We demonstrate our approach by providing challenging public
datasets and extending two open source projects to provide an end-to-end 3D
modeling baseline solution to stimulate further research and evaluation with a
public leaderboard.
