  Indoor rooms are among the most common use cases in 3D scene understanding.
Current state-of-the-art methods for this task are driven by large annotated
datasets. Room layouts are especially important, consisting of structural
elements in 3D, such as wall, floor, and ceiling. However, they are difficult
to annotate, especially on pure RGB video. We propose a novel method to produce
generic 3D room layouts just from 2D segmentation masks, which are easy to
annotate for humans. Based on these 2D annotations, we automatically
reconstruct 3D plane equations for the structural elements and their spatial
extent in the scene, and connect adjacent elements at the appropriate contact
edges. We annotate and publicly release 2246 3D room layouts on the
RealEstate10k dataset, containing YouTube videos. We demonstrate the high
quality of these 3D layouts annotations with extensive experiments.

Computer Vision and Pattern Recognition;Graphics