The CRS4 Visual Computing Group has recently developed a novel end-to-end approach to predict a 3D room layout from a single panoramic image. The new method, based on a new neural network architecture, outperforms state-of-the-art solutions in prediction accuracy, in particular in cases of complex wall layouts or curved wall footprints.

All the details of the method are described in the following article: Giovanni Pintore, Marco Agus, and Enrico Gobbetti. AtlantaNet: Inferring the 3D Indoor Layout from a Single 360 Image beyond the Manhattan World Assumption. In Proc. ECCV, August 2020. To appear. Article Preprint.

The research has received funding from Sardinian Regional Authorities under projects VIGECLAB, AMAC and TDM (POR FESR 2014-2020) and from the Europan Commission under the project EVOCATION (Horizon 2020, grant agreement N. 813170).