1 citations · 3 across the 10 of their papers we have counts for
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Drone Detection with Event Cameras
Gabriele Magrini, Lorenzo Berlincioni, Luca Cultrera +2
The diffusion of drones presents significant security and safety challenges. Traditional surveillance systems, particularly conventional frame-based cameras, struggle to reliably d…
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…
Spatio-temporal Transformers for Action Unit Classification with Event Cameras
Luca Cultrera, Federico Becattini, Lorenzo Berlincioni +2
Face analysis has been studied from different angles to infer emotion, poses, shapes, and landmarks. Traditionally RGB cameras are used, yet for fine-grained tasks standard sensors…
Neuromorphic Facial Analysis with Cross-Modal Supervision
Federico Becattini, Luca Cultrera, Lorenzo Berlincioni +3
Traditional approaches for analyzing RGB frames are capable of providing a fine-grained understanding of a face from different angles by inferring emotions, poses, shapes, landmark…
Garment Attribute Manipulation with Multi-level Attention
Vittorio Casula, Lorenzo Berlincioni, Luca Cultrera +5
In the rapidly evolving field of online fashion shopping, the need for more personalized and interactive image retrieval systems has become paramount. Existing methods often strugg…
Neuromorphic Face Analysis: a Survey
Federico Becattini, Lorenzo Berlincioni, Luca Cultrera +1
Neuromorphic sensors, also known as event cameras, are a class of imaging devices mimicking the function of biological visual systems. Unlike traditional frame-based cameras, which…
Neuromorphic Valence and Arousal Estimation
Lorenzo Berlincioni, Luca Cultrera, Federico Becattini +1
Recognizing faces and their underlying emotions is an important aspect of biometrics. In fact, estimating emotional states from faces has been tackled from several angles in the li…
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…
Neuromorphic Event-based Facial Expression Recognition
Lorenzo Berlincioni, Luca Cultrera, Chiara Albisani +5
Recently, event cameras have shown large applicability in several computer vision fields especially concerning tasks that require high temporal resolution. In this work, we investi…
Modelling the Statistics of Cyclic Activities by Trajectory Analysis on the Manifold of Positive-Semi-Definite Matrices
Ettore Maria Celozzi, Luca Ciabini, Luca Cultrera +4
In this paper, a model is presented to extract statistical summaries to characterize the repetition of a cyclic body action, for instance a gym exercise, for the purpose of checkin…
Explaining Autonomous Driving by Learning End-to-End Visual Attention
Luca Cultrera, Lorenzo Seidenari, Federico Becattini +2
Current deep learning based autonomous driving approaches yield impressive results also leading to in-production deployment in certain controlled scenarios. One of the most popular…