no code implementations • 28 Jul 2021 • Eugenio Lomurno, Andrea Romanoni, Matteo Matteucci
Today, Multi-View Stereo techniques are able to reconstruct robust and detailed 3D models, especially when starting from high-resolution images.
no code implementations • 1 Dec 2020 • Andrea Romanoni, Matteo Matteucci
The refinement step is applied for each facet using only the camera pair selected.
1 code implementation • ECCV 2020 • Marco Cannici, Marco Ciccone, Andrea Romanoni, Matteo Matteucci
Dynamic Vision Sensors (DVSs) asynchronously stream events in correspondence of pixels subject to brightness changes.
no code implementations • 21 May 2019 • Andrea Romanoni, Matteo Matteucci
Many Multi-View-Stereo algorithms extract a 3D mesh model of a scene, after fusing depth maps into a volumetric representation of the space.
no code implementations • ICCV 2019 • Andrea Romanoni, Matteo Matteucci
One of the most successful approaches in Multi-View Stereo estimates a depth map and a normal map for each view via PatchMatch-based optimization and fuses them into a consistent 3D points cloud.
no code implementations • 20 Feb 2019 • Luca Morreale, Andrea Romanoni, Matteo Matteucci
Dense 3D visual mapping estimates as many as possible pixel depths, for each image.
no code implementations • 26 Jul 2018 • Andrea Romanoni, Matteo Matteucci
Mesh labeling is the key problem of classifying the facets of a 3D mesh with a label among a set of possible ones.
no code implementations • 25 Jul 2018 • Marco Cannici, Marco Ciccone, Andrea Romanoni, Matteo Matteucci
Event-based cameras are neuromorphic sensors capable of efficiently encoding visual information in the form of sparse sequences of events.
no code implementations • 21 May 2018 • Marco Cannici, Marco Ciccone, Andrea Romanoni, Matteo Matteucci
Event-based cameras, also known as neuromorphic cameras, are bioinspired sensors able to perceive changes in the scene at high frequency with low power consumption.
1 code implementation • 16 May 2018 • Luca Morreale, Andrea Romanoni, Matteo Matteucci
Finding the best poses to capture part of the scene is one of the most challenging topic that goes under the name of Next Best View.
1 code implementation • 17 Jan 2018 • Andrea Bignoli, Andrea Romanoni, Matteo Matteucci
This paper presents a novel method for the reconstruction of 3D edges in multi-view stereo scenarios.
no code implementations • 18 Aug 2017 • Andrea Romanoni, Daniele Fiorenti, Matteo Matteucci
In the era of autonomous driving, urban mapping represents a core step to let vehicles interact with the urban context.
no code implementations • 16 Aug 2017 • Andrea Romanoni, Marco Ciccone, Francesco Visin, Matteo Matteucci
In this paper we propose a novel method to refine both the geometry and the semantic labeling of a given mesh.
no code implementations • 29 Sep 2016 • Gheorghii Postica, Andrea Romanoni, Matteo Matteucci
Detecting moving objects in dynamic scenes from sequences of lidar scans is an important task in object tracking, mapping, localization, and navigation.
no code implementations • 21 Apr 2016 • Andrea Romanoni, Matteo Matteucci
Urban reconstruction from a video captured by a surveying vehicle constitutes a core module of automated mapping.
no code implementations • 21 Apr 2016 • Andrea Romanoni, Amaël Delaunoy, Marc Pollefeys, Matteo Matteucci
In this paper we propose a new approach to incrementally initialize a manifold surface for automatic 3D reconstruction from images.
no code implementations • 20 Jul 2015 • Andrea Romanoni, Matteo Matteucci
From the 3D Delaunay triangulation of these points, state-of-the-art algorithms build a manifold rough model of the scene.