23 citations · 42 across the 13 of their papers we have counts for
13 papers
MamMA: A Mamba-Based Pedestrian Trajectory Prediction Algorithm Considering Occupancy Map and Pedestrian Awareness States
Juncen Long, Xiaofeng Jin, Gianluca Bardaro +2
Many pedestrian trajectory prediction algorithms have been proposed to improve the safety of navigation for mobile robots working in human-robot coexistence environments. Some pede…
Graph it first! Enabling Reasoning on Long-form Egocentric Videos through Scene Graphs
Agnese Taluzzi, Riccardo Santambrogio, Simone Mentasti +2
Existing multi-modal large language models (MLLMs) face significant challenges in processing long video sequences due to strict input token limitations. As a result, current video…
SGR-OCC: Evolving Monocular Priors for Embodied 3D Occupancy Prediction via Soft-Gating Lifting and Semantic-Adaptive Geometric Refinement
Yiran Guo, Simone Mentasti, Xiaofeng Jin +2
3D semantic occupancy prediction is a cornerstone for embodied AI, enabling agents to perceive dense scene geometry and semantics incrementally from monocular video streams. Howeve…
EETnet: a CNN for Gaze Detection and Tracking for Smart-Eyewear
Andrea Aspesi, Andrea Simpsi, Aaron Tognoli +3
Event-based cameras are becoming a popular solution for efficient, low-power eye tracking. Due to the sparse and asynchronous nature of event data, they require less processing pow…
From Pixels to Graphs: using Scene and Knowledge Graphs for HD-EPIC VQA Challenge
Agnese Taluzzi, Davide Gesualdi, Riccardo Santambrogio +4
This report presents SceneNet and KnowledgeNet, our approaches developed for the HD-EPIC VQA Challenge 2025. SceneNet leverages scene graphs generated with a multi-modal large lang…
High-frequency near-eye ground truth for event-based eye tracking
Andrea Simpsi, Andrea Aspesi, Simone Mentasti +3
Event-based eye tracking is a promising solution for efficient and low-power eye tracking in smart eyewear technologies. However, the novelty of event-based sensors has resulted in…
A Spatio-temporal Graph Network Allowing Incomplete Trajectory Input for Pedestrian Trajectory Prediction
Juncen Long, Gianluca Bardaro, Simone Mentasti +1
Pedestrian trajectory prediction is important in the research of mobile robot navigation in environments with pedestrians. Most pedestrian trajectory prediction algorithms require…
RadarLCD: Learnable Radar-based Loop Closure Detection Pipeline
Mirko Usuelli, Matteo Frosi, Paolo Cudrano +2
Loop Closure Detection (LCD) is an essential task in robotics and computer vision, serving as a fundamental component for various applications across diverse domains. These applica…
Extended Object Tracking in Curvilinear Road Coordinates for Autonomous Driving
Pragyan Dahal, Simone Mentasti, Stefano Arrigoni +3
In literature, Extended Object Tracking (EOT) algorithms developed for autonomous driving predominantly provide obstacles state estimation in cartesian coordinates in the Vehicle R…
Two algorithms for vehicular obstacle detection in sparse pointcloud
Simone Mentasti, Matteo Matteucci, Stefano Arrigoni +1
One of the main components of an autonomous vehicle is the obstacle detection pipeline. Most prototypes, both from research and industry, rely on lidars for this task. Pointcloud i…
Design of a prototypical platform for autonomous and connected vehicles
Stefano Arrigoni, Simone Mentasti, Federico Cheli +2
Self-driving technology is expected to revolutionize different sectors and is seen as the natural evolution of road vehicles. In the last years, real-world validation of designed a…
LiDAR point-cloud processing based on projection methods: a comparison
Guidong Yang, Simone Mentasti, Mattia Bersani +3
An accurate and rapid-response perception system is fundamental for autonomous vehicles to operate safely. 3D object detection methods handle point clouds given by LiDAR sensors to…
Advances in centerline estimation for autonomous lateral control
Paolo Cudrano, Simone Mentasti, Matteo Matteucci +3
The ability of autonomous vehicles to maintain an accurate trajectory within their road lane is crucial for safe operation. This requires detecting the road lines and estimating th…