406 citations · 667 across the 7 of their papers we have counts for
8 papers
E(GO)MOTION: Motion Augmented Event Stream for Egocentric Action Recognition
Chiara Plizzari, Mirco Planamente, Gabriele Goletto +4
Event cameras are novel bio-inspired sensors, which asynchronously capture pixel-level intensity changes in the form of "events". Due to their sensing mechanism, event cameras have…
Neural Weighted A*: Learning Graph Costs and Heuristics with Differentiable Anytime A*
Alberto Archetti, Marco Cannici, Matteo Matteucci
Recently, the trend of incorporating differentiable algorithms into deep learning architectures arose in machine learning research, as the fusion of neural layers and algorithmic l…
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…
Spatial Temporal Transformer Network for Skeleton-based Action Recognition
Chiara Plizzari, Marco Cannici, Matteo Matteucci
Skeleton-based human action recognition has achieved a great interest in recent years, as skeleton data has been demonstrated to be robust to illumination changes, body scales, dyn…
Skeleton-based Action Recognition via Spatial and Temporal Transformer Networks
Chiara Plizzari, Marco Cannici, Matteo Matteucci
Skeleton-based Human Activity Recognition has achieved great interest in recent years as skeleton data has demonstrated being robust to illumination changes, body scales, dynamic c…
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…
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…
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…