The Pattern Analysis and Computer Vision (PAVIS) research line is actively developing an artificial intelligence (AI) infrastructure to understand our physical space and the human behaviors within it.
The focus is on creating intelligent systems that jointly accomplish two main goals:
Pattern Analysis and Computer Vision
Spatial AI
Perceive and understand autonomously the real physical world, both static and dynamic, with its corresponding spatial semantic (where are things, what is their function, which is the dynamic of the scene).
Social AI
Perceive and understand humans and their behaviors as observed by cameras in relation to the physical spaces they are interacting with.
Last Publications
2023
Mohammadi S. S., Duarte N. F., Dimou D., Wang Y., Taiana M., Morerio P., Dehban A., Moreno P., Bernardino A., Del Bue A., Santos-Victor J.
3DSGrasp: 3D Shape-Completion for Robotic Grasp
2023 IEEE International Conference on Robotics and Automation (ICRA), pp. 6
2023
Savian S., Elahi M., Janes A., Tillo T.
Benchmarking equivariance for Deep Learning based optical flow estimators
Signal Processing: Image Communication
2023
Daoudi M., Harandi M., Murino V.
Guest Editorial : Learning with Manifolds in Computer Vision
Image and Vision Computing, vol. 129
Videos
Intelligent Sensor Network for assistive AI Research
Introduction to MEMEX Project
Aworld - AI powered visual localization
PAVIS - Overview
SceneUnderLight - IIT - UNIVR - OSRAM
Drone Localization with Augmented Acoustic Imaging
Principal Investigator
Pattern Analysis and Computer Vision