Giovanni Pintore — accepted AI-conference papers

2021

SliceNet: Deep Dense Depth Estimation From a Single Indoor Panorama Using a Slice-Based Representation

Giovanni Pintore, Marco Agus, Eva Almansa, Jens Schneider, Enrico Gobbetti

CVPR 2021poster

We introduce a novel deep neural network to estimate a depth map from a single monocular indoor panorama. The network directly works on the equirectangular projection, exploiting the properties of indoor 360 images. Starting from the fact that gravity plays an important role in the design and constr…

Cited by 109 PDF ↗Scholar ↗

2020

AtlantaNet: Inferring the 3D Indoor Layout from a Single 360(∘) Image beyond the Manhattan World Assumption

Giovanni Pintore, Marco Agus, Enrico Gobbetti

ECCV 2020poster

We introduce a novel end-to-end approach to predict a 3D room layout from a single panoramic image. Compared to recent state-of-the-art works, our method is not limited to Manhattan World environments, and can reconstruct rooms bounded by vertical walls that do not form right angles or are curved --…

Cited by 89 Source ↗PDF ↗code ↗Scholar ↗