  We present a novel method to reconstruct the 3D layout of a room (walls,
floors, ceilings) from a single perspective view in challenging conditions, by
contrast with previous single-view methods restricted to cuboid-shaped layouts.
This input view can consist of a color image only, but considering a depth map
results in a more accurate reconstruction. Our approach is formalized as
solving a constrained discrete optimization problem to find the set of 3D
polygons that constitute the layout. In order to deal with occlusions between
components of the layout, which is a problem ignored by previous works, we
introduce an analysis-by-synthesis method to iteratively refine the 3D layout
estimate. As no dataset was available to evaluate our method quantitatively, we
created one together with several appropriate metrics. Our dataset consists of
293 images from ScanNet, which we annotated with precise 3D layouts. It offers
three times more samples than the popular NYUv2 303 benchmark, and a much
larger variety of layouts.
