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.
Source: InteriorNet: Mega-scale Multi-sensor Photo-realistic Indoor Scenes Dataset


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