65 citations · 66 across the 5 of their papers we have counts for
5 papers · 1 filter
On the Design of Privacy-Aware Cameras: a Study on Deep Neural Networks
Marcela Carvalho, Oussama Ennaffi, Sylvain Chateau +1
In spite of the legal advances in personal data protection, the issue of private data being misused by unauthorized entities is still of utmost importance. To prevent this, Privacy…
Pix2Point: Learning Outdoor 3D Using Sparse Point Clouds and Optimal Transport
Rémy Leroy, Pauline Trouvé-Peloux, Frédéric Champagnat +2
Good quality reconstruction and comprehension of a scene rely on 3D estimation methods. The 3D information was usually obtained from images by stereo-photogrammetry, but deep learn…
Multi-Task Learning of Height and Semantics from Aerial Images
Marcela Carvalho, Bertrand Le Saux, Pauline Trouvé-Peloux +2
Aerial or satellite imagery is a great source for land surface analysis, which might yield land use maps or elevation models. In this investigation, we present a neural network fra…
Technical Report: Co-learning of geometry and semantics for online 3D mapping
Marcela Carvalho, Maxime Ferrera, Alexandre Boulch +3
This paper is a technical report about our submission for the ECCV 2018 3DRMS Workshop Challenge on Semantic 3D Reconstruction \cite{Tylecek2018rms}. In this paper, we address 3D s…
Deep Depth from Defocus: how can defocus blur improve 3D estimation using dense neural networks?
Marcela Carvalho, Bertrand Le Saux, Pauline Trouvé-Peloux +2
Depth estimation is of critical interest for scene understanding and accurate 3D reconstruction. Most recent approaches in depth estimation with deep learning exploit geometrical s…