English

PanoRoom: From the Sphere to the 3D Layout

Computer Vision and Pattern Recognition 2018-08-30 v1

Abstract

We propose a novel FCN able to work with omnidirectional images that outputs accurate probability maps representing the main structure of indoor scenes, which is able to generalize on different data. Our approach handles occlusions and recovers complex shaped rooms more faithful to the actual shape of the real scenes. We outperform the state of the art not only in accuracy of the 3D models but also in speed.

Keywords

Cite

@article{arxiv.1808.09879,
  title  = {PanoRoom: From the Sphere to the 3D Layout},
  author = {Clara Fernandez-Labrador and Jose M. Facil and Alejandro Perez-Yus and Cedric Demonceaux and Jose J. Guerrero},
  journal= {arXiv preprint arXiv:1808.09879},
  year   = {2018}
}
R2 v1 2026-06-23T03:48:05.814Z