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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 2018Show all

7 papers · 1 filter

cs.CV2018

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…

cs.CV2018

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…

cs.CV2018

ReConvNet: Video Object Segmentation with Spatio-Temporal Features Modulation

Francesco Lattari, Marco Ciccone, Matteo Matteucci +2

We introduce ReConvNet, a recurrent convolutional architecture for semi-supervised video object segmentation that is able to fast adapt its features to focus on any specific object…

cs.CV2018

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…

cs.CV2018

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…

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…