Funded Projects
Egocentric VIsual PROcedural Reasoning for usEr aSsistance (EVIPRORES)
PI: Antonino Furnari
EVIPRORES investigates visual procedural reasoning from egocentric observations, with the goal of enabling AI systems that can interpret task structure and support users during complex activities.
Tracking in Egovision for Applied Memory (TEAM)
Associate PI: Antonino Furnari
TEAM studies tracking-based methods for applied memory in egocentric vision. The project explores how object-level cues in first-person video can support long-term memory representations for AI systems.
EXTRA EYE — Egocentric and eXocenTRic views for object-level human behavior analysis and understanding through tracking in complex spaces
Associate PI: Antonino Furnari
EXTRA EYE addresses object-centric human behaviour analysis across egocentric and exocentric views. The project investigates how tracking and cross-view reasoning can improve activity understanding in complex real-world environments.
EgoRecall — Streaming Episodic Memory for Egocentric AI
PI: Antonino Furnari
EgoRecall investigates streaming episodic memory for egocentric AI systems. The project was selected for the NVIDIA Academic Grant Program, which is donating two DGX Spark units to support this research.