23 citations · 47 across the 9 of their papers we have counts for
18 papers
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…
Facetwise Mesh Refinement for Multi-View Stereo
Andrea Romanoni, Matteo Matteucci
Mesh refinement is a fundamental step for accurate Multi-View Stereo. It modifies the geometry of an initial manifold mesh to minimize the photometric error induced in a set of cam…
A Differentiable Recurrent Surface for Asynchronous Event-Based Data
Marco Cannici, Marco Ciccone, Andrea Romanoni +1
Dynamic Vision Sensors (DVSs) asynchronously stream events in correspondence of pixels subject to brightness changes. Differently from classic vision devices, they produce a sparse…
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…
TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo
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 3…
Dense 3D Visual Mapping via Semantic Simplification
Luca Morreale, Andrea Romanoni, Matteo Matteucci
Dense 3D visual mapping estimates as many as possible pixel depths, for each image. This results in very dense point clouds that often contain redundant and noisy information, espe…
A Data-driven Prior on Facet Orientation for Semantic Mesh Labeling
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. State-of-the-art methods model mesh labeling as a Markov Random F…
Attention Mechanisms for Object Recognition with Event-Based Cameras
Marco Cannici, Marco Ciccone, Andrea Romanoni +1
Event-based cameras are neuromorphic sensors capable of efficiently encoding visual information in the form of sparse sequences of events. Being biologically inspired, they are com…
Predicting the Next Best View for 3D Mesh Refinement
Luca Morreale, Andrea Romanoni, Matteo Matteucci
3D reconstruction is a core task in many applications such as robot navigation or sites inspections. Finding the best poses to capture part of the scene is one of the most challeng…
Asynchronous Convolutional Networks for Object Detection in Neuromorphic Cameras
Marco Cannici, Marco Ciccone, Andrea Romanoni +1
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. Becoming availa…
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…
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…
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…
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…
Robust Moving Objects Detection in Lidar Data Exploiting Visual Cues
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. Many works focus on changes…
Incremental Reconstruction of Urban Environments by Edge-Points Delaunay Triangulation
Andrea Romanoni, Matteo Matteucci
Urban reconstruction from a video captured by a surveying vehicle constitutes a core module of automated mapping. When computational power represents a limited resource and, a deta…
Automatic 3D Reconstruction of Manifold Meshes via Delaunay Triangulation and Mesh Sweeping
Andrea Romanoni, Amaël Delaunoy, Marc Pollefeys +1
In this paper we propose a new approach to incrementally initialize a manifold surface for automatic 3D reconstruction from images. More precisely we focus on the automatic initial…
Efficient moving point handling for incremental 3D manifold reconstruction
Andrea Romanoni, Matteo Matteucci
As incremental Structure from Motion algorithms become effective, a good sparse point cloud representing the map of the scene becomes available frame-by-frame. From the 3D Delaunay…