4 papers
Spike-TBR: a Noise Resilient Neuromorphic Event Representation
Gabriele Magrini, Federico Becattini, Luca Cultrera +3
Event cameras offer significant advantages over traditional frame-based sensors, including higher temporal resolution, lower latency and dynamic range. However, efficiently convert…
FRED: The Florence RGB-Event Drone Dataset
Gabriele Magrini, Niccolò Marini, Federico Becattini +4
Small, fast, and lightweight drones present significant challenges for traditional RGB cameras due to their limitations in capturing fast-moving objects, especially under challengi…
EV-Flying: an Event-based Dataset for In-The-Wild Recognition of Flying Objects
Gabriele Magrini, Federico Becattini, Giovanni Colombo +1
Monitoring aerial objects is crucial for security, wildlife conservation, and environmental studies. Traditional RGB-based approaches struggle with challenges such as scale variati…
Addressing Limitations of State-Aware Imitation Learning for Autonomous Driving
Luca Cultrera, Federico Becattini, Lorenzo Seidenari +2
Conditional Imitation learning is a common and effective approach to train autonomous driving agents. However, two issues limit the full potential of this approach: (i) the inertia…