InteriorNet is a RGB-D for large scale interior scene understanding and mapping. The dataset contains 20M images created by pipeline:
(A) the authors collected around 1 million CAD models provided by world-leading furniture manufacturers.
(B) based on those models, around 1,100 professional designers create around 22 million interior layouts. Most of such layouts have been used in real-world decorations.
(C) For each layout, authors generate a number of configurations to represent different random lightings and simulation of scene change over time in daily life.
(D) Authors provide an interactive simulator (ViSim) to help for creating ground truth IMU, events, as well as monocular or stereo camera trajectories including hand-drawn, random walking and neural network based realistic trajectory.
(E) All supported image sequences and ground truth.