activity
20162019
most citedMesh-based Camera Pairs Selection and Occlusion-Aware Masking for Mesh Refinement

13 citations · 20 across the 3 of their papers we have counts for

collaborators

8 papers

cs.RO20192 cited

Towards Affordance Prediction with Vision via Task Oriented Grasp Quality Metrics

Luca Cavalli, Gianpaolo Di Pietro, Matteo Matteucci

While many quality metrics exist to evaluate the quality of a grasp by itself, no clear quantification of the quality of a grasp relatively to the task the grasp is used for has be…

cs.CV201913 cited

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

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. Due to the limited scalability of such…

cs.CV2018

Multi-View Stereo 3D Edge Reconstruction

Andrea Bignoli, Andrea Romanoni, Matteo Matteucci

This paper presents a novel method for the reconstruction of 3D edges in multi-view stereo scenarios. Previous research in the field typically relied on video sequences and limited…

cs.RO20185 cited

Real-time CPU-based large-scale 3D mesh reconstruction

Enrico Piazza, Andrea Romanoni, Matteo Matteucci

In Robotics, especially in this era of autonomous driving, mapping is one key ability of a robot to be able to navigate through an environment, localize on it and analyze its trave…

cs.CV2017

Multi-View Stereo with Single-View Semantic Mesh Refinement

Andrea Romanoni, Marco Ciccone, Francesco Visin +1

While 3D reconstruction is a well-established and widely explored research topic, semantic 3D reconstruction has only recently witnessed an increasing share of attention from the C…

cs.CV2017

Mesh-based 3D Textured Urban Mapping

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. Successful mapping algorithms have been proposed in the last…