Search Results for author: Andrea Romanoni

Found 17 papers, 3 papers with code

Improving Multi-View Stereo via Super-Resolution

no code implementations28 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.

Super-Resolution

Facetwise Mesh Refinement for Multi-View Stereo

no code implementations1 Dec 2020 Andrea Romanoni, Matteo Matteucci

The refinement step is applied for each facet using only the camera pair selected.

3D Reconstruction

A Differentiable Recurrent Surface for Asynchronous Event-Based Data

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.

Optical Flow Estimation

Mesh-based Camera Pairs Selection and Occlusion-Aware Masking for Mesh Refinement

no code implementations21 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.

TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo

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.

A Data-driven Prior on Facet Orientation for Semantic Mesh Labeling

no code implementations26 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.

Attention Mechanisms for Object Recognition with Event-Based Cameras

no code implementations25 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.

Event-based vision Object Recognition +1

Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras

no code implementations21 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.

Object object-detection +1

Predicting the Next Best View for 3D Mesh Refinement

1 code implementation16 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.

3D Reconstruction Robot Navigation

Multi-View Stereo 3D Edge Reconstruction

1 code implementation17 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.

Mesh-based 3D Textured Urban Mapping

no code implementations18 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.

Autonomous Driving Surface Reconstruction

Multi-View Stereo with Single-View Semantic Mesh Refinement

no code implementations16 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.

3D Reconstruction

Robust Moving Objects Detection in Lidar Data Exploiting Visual Cues

no code implementations29 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.

Object Tracking

Automatic 3D Reconstruction of Manifold Meshes via Delaunay Triangulation and Mesh Sweeping

no code implementations21 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.

3D Reconstruction

Incremental Reconstruction of Urban Environments by Edge-Points Delaunay Triangulation

no code implementations21 Apr 2016 Andrea Romanoni, Matteo Matteucci

Urban reconstruction from a video captured by a surveying vehicle constitutes a core module of automated mapping.

Efficient moving point handling for incremental 3D manifold reconstruction

no code implementations20 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.

3D Reconstruction Management

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