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Perception and Intelligence Laboratory (PINlab)

Department of Computer Science

Sapienza University of Rome, Italy

Computer vision and machine learning have great potential to endow machines/robots with the (visual) perception of the environment and the intelligence to reason about it, and take decisions. The field has thrived in the past three decades, and it stands now as one of the key technological ingredients for autonomous driving, unmanned drones, and human-robot-collaboration, as well as the pervasive novel asset for other fields of science, including earthquake and weather forecasting.

Our lab is interested in fundamental research and innovation transfer on computer vision and machine learning. Our specific research interests include distributed and multi-agent intelligent systems, perception (detection, recognition, re-identification, forecasting), and general intelligence (reasoning, meta-learning, domain adaptation), within sustainable (low-power-consumption and constrained-computational-resource sensors and devices) and interpretable (interpretable and verifiable AI) frameworks.

RECENT PUBLICATIONS

[All Publications]
  1. Luca Scofano,  Alessio Sampieri,  Tommaso Campari,  Valentino Sacco,  Indro Spinelli,  Lamberto Ballan,  and Fabio Galasso
    Following the Human Thread in Social Navigation
    In International Conference on Learning Representation, 2025
  2. Avik Pal,  Max Spengler,  Guido Maria D’Amely Melendugno,  Alessandro Flaborea,  Fabio Galasso,  and Pascal Mettes
    Compositional Entailment Learning for Hyperbolic Vision-Language Models
    In International Conference on Learning Representation, 2025
  3. Laura Laurenti,  Gabriele Paoletti,  Elisa Tinti,  Fabio Galasso,  Cristiano Collettini,  and Chris Marone
    Probing the evolution of fault properties during the seismic cycle with deep learning
    Nature Communications, 2024
  4. Daniele Trappolini,  Laura Laurenti,  Giulio Poggiali,  Elisa Tinti,  Fabio Galasso,  Michelini Alberto,  and Chris Marone
    Cold Diffusion Model for Seismic Denoising
    Journal of Geophysical Research: Machine Learning and Computation, 2024
  5. Muhammad Rameez Ur Rahman,  Jhony H. Giraldo,  Indro Spinelli,  Stéphane Lathuilière,  and Fabio Galasso
    OVOSE: Open-Vocabulary Semantic Segmentation in Event-Based Cameras
    In International Conference on Pattern Recognition (ICPR), 2024