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20172025
most citedCoordination in Adversarial Sequential Team Games via Multi-Agent Deep Reinforcement Learning

4 citations · 18 across the 12 of their papers we have counts for

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8 papers · 1 filter

cs.CV2023★ 1 cited

FedDrive v2: an Analysis of the Impact of Label Skewness in Federated Semantic Segmentation for Autonomous Driving

Eros Fanì, Marco Ciccone, Barbara Caputo

We propose FedDrive v2, an extension of the Federated Learning benchmark for Semantic Segmentation in Autonomous Driving. While the first version aims at studying the effect of dom…

cs.CV2022★ 3 cited

Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning

Donald Shenaj, Eros Fanì, Marco Toldo +6

Federated Learning (FL) has recently emerged as a possible way to tackle the domain shift in real-world Semantic Segmentation (SS) without compromising the private nature of the co…

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…

cs.CV2020

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…

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…