Study of human pose
We study pose in videos and derive 2D and 3D information on the anatomical joints, the estimated head direction, and prototypical poses.
MLV
We investigate different nuances of visual perception in artificial intelligence systems, where computer vision and machine learning are combined to obtain robust data-driven methods addressing a variety of problems.
In this multidisciplinary world, we are interested in mathematically sound algorithms, computational models, and a wide range of applications.
In particular, we study and develop methods for scene understanding, motion analysis, and action recognition, with applications to assisted living, human-machine interaction, and robotics.
Research topics
Cognitively inspired motion understanding
We are interested in the strong interplay between visual computation and cognitive science. We apply our research in particular to HRI.
Scene analysis
We analyse the scene, detecting and tracking objects in 2D and 3D, with a focus on efficiency and on working under limited resources.
Collaborative projects
We bring our expertise in computer vision and machine learning on a variety of projects.
Computer vision for biomedical data challenges
We explore machine learning and computer vision solutions to challenges typical of biological and medical data, including learning with limited or no labels and interpretability. We design and implement methods for the solution of a broad range of biomedical data related applications.
People
Nicoletta
NocetiFrancesca
OdoneVito Paolo
PastoreMatteo
MoroJacopo
DapuetoYara
Abdelmott…Khan
DadanManasa
PawarRoberto
Di ViaMassimiliano
CiranniMatteo
InterlandoXiaolin
XingGabriele
BortolaiVeronica
PignedoliGuido
VallarinoMohammad
Zohaib
Past People
People
Davide Marinelli | 2025 | Research Scholar | Machine Learning, Computer Vision
Ani Gjergji | 2024 → 2025 | Research Scholar | Machine Learning, Computer Vision
Paolo Didier Alfano | 2023 → 2025 | Post-doctoral fellow | Machine Learning and Vision
Larbi Touijer | 2021 → 2025 | PhD student | Deep Learning for Medical Image Analysis
Federico Figari Tomenotti | 2023 → 2024 | Post-doctoral fellow | Computer Vision, Machine Learning
Alexander Statsenko | 2022 → 2024 | Research Scholar | Machine Learning applications
Federico Figari Tomenotti | 2020 → 2024 | PhD student | Computer Vision
Alessandro Piazza | 2024 | Student
Massimiliano Ciranni | 2023 | Research Scholar | Computer Vision
Clara Mouawad | 2023 | Student
Elena Vincenzi | 2020 → 2023 | PhD student | Medical Image Analysis
Issa Mouawad | 2022 → 2023 | Research Scholar | Computer Vision, Machine Learning
Simone Testa | 2023 | Post-doctoral fellow | Medical Image Analysis
Elena Nicora | 2022 → 2023 | Post-doctoral fellow | Computer Vision
Luca Garello | 2022 → 2023 | PhD student | Vision and robotics
Matteo Moro | 2022 → 2023 | Post-doctoral fellow | Computer Vision
Massimiliano Ciranni | 2023 | Student
Simone Campisi | 2022 | Research Scholar
Matteo Ghirardelli | 2022 | Student
Issa Mouawad | 2022 | PhD student | Computer Vision
Research projects
Most recent MLV research projects
- MARCH
Multi-modal learning for gait-based human analysis and authentication
Unit MLVLeading scientist Nicoletta Noceti, Francesca OdoneRole within the project Principal InvestigatorDuration 2023 - 2026Sponsors AFOSRTotal funding 299 k€ - CLOSED
Cognitively-inspired architectures for human motion understanding
Unit MLVLeading scientist Nicoletta NocetiRole within the project Principal InvestigatorDuration 2020 - 2023Sponsors AFOSRTotal funding 163 k€ - CLOSED
EFFICACITY
Unit MLVLeading scientist Nicoletta NocetiRole within the project Principal InvestigatorDuration 2021 - 2023Sponsors POR FESR Liguria (C,CG,C)Total funding 63 k€ - CLOSED
Undroid (Underwater Droid)
Unit MLVLeading scientist Francesca OdoneRole within the project Principal InvestigatorDuration 2021 - 2023Sponsors POR FESR Liguria (BK)Total funding 70 k€
Publications
Most recent MLV publications
| Title | Year | Author | Venue |
|---|---|---|---|
| Anomaly detection in feature space for detecting changes in phytoplankton populations | 2024 | Ciranni M.; Odone F.; Pastore V. P. | FRONTIERS IN MARINE SCIENCE |
| Looking at Model Debiasing through the Lens of Anomaly Detection | 2024 | VP Pastore M Ciranni D Marinelli F Odone V Murino | ArXiv Preprint |
| Self-supervised pre-training with diffusion model for few-shot landmark detection in x-ray images | 2024 | R Di Via F Odone VP Pastore | ArXiv Preprint |
| Anticipation through Head Pose Estimation: a preliminary study | 2024 | FF Tomenotti N Noceti | ArXiv Preprint |
| Say My Name: a Model’s Bias Discovery Framework | 2024 | Massimiliano Ciranni Luca Molinaro Carlo Alberto Barbano Attilio Fiandrotti Vittorio Murino Vito Paolo Pastore Enzo Tartaglione | ArXiv Preprint |