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20162021
most citedMesh-based Camera Pairs Selection and Occlusion-Aware Masking for Mesh Refinement

13 citations · 22 across the 9 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.RO2021

Two algorithms for vehicular obstacle detection in sparse pointcloud

Simone Mentasti, Matteo Matteucci, Stefano Arrigoni +1

One of the main components of an autonomous vehicle is the obstacle detection pipeline. Most prototypes, both from research and industry, rely on lidars for this task. Pointcloud i…

cs.RO2021

ART-SLAM: Accurate Real-Time 6DoF LiDAR SLAM

Matteo Frosi, Matteo Matteucci

Real-time six degree-of-freedom pose estimation with ground vehicles represents a relevant and well studied topic in robotics, due to its many applications, such as autonomous driv…

cs.CV2021

Improving Multi-View Stereo via Super-Resolution

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. However, there are cases in which t…

cs.IT2021

Position-agnostic Algebraic Estimation of 6G V2X MIMO Channels via Unsupervised Learning

Lorenzo Cazzella, Dario Tagliaferri, Marouan Mizmizi +4

MIMO systems in the context of 6G Vehicle-to-Everything (V2X) will require an accurate channel knowledge to enable efficient communication. Standard channel estimation techniques,…

cs.CV2021

DA4Event: towards bridging the Sim-to-Real Gap for Event Cameras using Domain Adaptation

Mirco Planamente, Chiara Plizzari, Marco Cannici +5

Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". The innovative way they acquire data presents seve…

eess.SP2021

Probabilistic electric load forecasting through Bayesian Mixture Density Networks

Alessandro Brusaferri, Matteo Matteucci, Stefano Spinelli +1

Probabilistic load forecasting (PLF) is a key component in the extended tool-chain required for efficient management of smart energy grids. Neural networks are widely considered to…