321 citations · 721 across the 36 of their papers we have counts for
42 papers
R2RI: A Multi-View Event and RGB Dataset for Robot-to-Robot Interaction
Gabriele Magrini, Riccardo Catalini, Federico Becattini +4
Understanding and modeling interactions between autonomous agents is a fundamental challenge in robotics, with broad implications for collaborative systems, social robotics, and hu…
Defending from GeoLocalization through Adversarial Road Trips
Niccolò Niccoli, Federico Becattini, Lorenzo Seidenari
Retrieval-based image geolocalization has emerged as a powerful technique for determining the location of a query image by matching it against a large, geotagged database. The succ…
Multiview Progress Prediction of Robot Activities
Elena Zoppellari, Federico Becattini, Marco Fiorucci +1
For robots to operate effectively and safely alongside humans, they must be able to understand the progress of ongoing actions. This ability, known as action progress prediction, i…
PEPR: Privileged Event-based Predictive Regularization for Domain Generalization
Gabriele Magrini, Federico Becattini, Niccolò Biondi +1
Deep neural networks for visual perception are highly susceptible to domain shift, which poses a critical challenge for real-world deployment under conditions that differ from the…
Immunizing Images from Text to Image Editing via Adversarial Cross-Attention
Matteo Trippodo, Federico Becattini, Lorenzo Seidenari
Recent advances in text-based image editing have enabled fine-grained manipulation of visual content guided by natural language. However, such methods are susceptible to adversaria…
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…
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…
Attacking Attention of Foundation Models Disrupts Downstream Tasks
Hondamunige Prasanna Silva, Federico Becattini, Lorenzo Seidenari
Foundation models represent the most prominent and recent paradigm shift in artificial intelligence. Foundation models are large models, trained on broad data that deliver high acc…
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 Drone Detection: an Event-RGB Multimodal Approach
Gabriele Magrini, Federico Becattini, Pietro Pala +2
In recent years, drone detection has quickly become a subject of extreme interest: the potential for fast-moving objects of contained dimensions to be used for malicious intents or…
Depth-based Privileged Information for Boosting 3D Human Pose Estimation on RGB
Alessandro Simoni, Francesco Marchetti, Guido Borghi +6
Despite the recent advances in computer vision research, estimating the 3D human pose from single RGB images remains a challenging task, as multiple 3D poses can correspond to the…
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…
Prompt and Prejudice
Lorenzo Berlincioni, Luca Cultrera, Federico Becattini +2
This paper investigates the impact of using first names in Large Language Models (LLMs) and Vision Language Models (VLMs), particularly when prompted with ethical decision-making t…
Interactive Garment Recommendation with User in the Loop
Federico Becattini, Xiaolin Chen, Andrea Puccia +4
Recommending fashion items often leverages rich user profiles and makes targeted suggestions based on past history and previous purchases. In this paper, we work under the assumpti…
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…
FLODCAST: Flow and Depth Forecasting via Multimodal Recurrent Architectures
Andrea Ciamarra, Federico Becattini, Lorenzo Seidenari +1
Forecasting motion and spatial positions of objects is of fundamental importance, especially in safety-critical settings such as autonomous driving. In this work, we address the is…
Deepfake detection by exploiting surface anomalies: the SurFake approach
Andrea Ciamarra, Roberto Caldelli, Federico Becattini +2
The ever-increasing use of synthetically generated content in different sectors of our everyday life, one for all media information, poses a strong need for deepfake detection tool…
Diffusion Based Augmentation for Captioning and Retrieval in Cultural Heritage
Dario Cioni, Lorenzo Berlincioni, Federico Becattini +1
Cultural heritage applications and advanced machine learning models are creating a fruitful synergy to provide effective and accessible ways of interacting with artworks. Smart aud…
3D Pose Nowcasting: Forecast the Future to Improve the Present
Alessandro Simoni, Francesco Marchetti, Guido Borghi +4
Technologies to enable safe and effective collaboration and coexistence between humans and robots have gained significant importance in the last few years. A critical component use…
ECO: Ensembling Context Optimization for Vision-Language Models
Lorenzo Agnolucci, Alberto Baldrati, Francesco Todino +3
Image recognition has recently witnessed a paradigm shift, where vision-language models are now used to perform few-shot classification based on textual prompts. Among these, the C…