collaborators

7 papers

cs.CV2026

EgoInteract: Synthetic Egocentric Videos Generation for Interaction Understanding and Anticipation

Rosario Leonardi, Francesco Ragusa, Daniele Materia +4

Collecting large-scale egocentric video datasets with dense spatial and temporal annotations is costly, slow, and often constrained by environmental biases, privacy constraints, an…

cs.CV2026

Leveraging Gaze and Set-of-Mark in VLLMs for Human-Object Interaction Anticipation from Egocentric Videos

Daniele Materia, Francesco Ragusa, Giovanni Maria Farinella

The ability to anticipate human-object interactions is highly desirable in an intelligent assistive system in order to guide users during daily life activities and understand their…

cs.CV2026

Leveraging Synthetic Data for Enhancing Egocentric Hand-Object Interaction Detection

Rosario Leonardi, Antonino Furnari, Francesco Ragusa +1

In this work, we explore the role of synthetic data in improving the detection of Hand-Object Interactions from egocentric images. Through extensive experimentation and comparative…

cs.CV2026

ENIGMA-360: An Ego-Exo Dataset for Human Behavior Understanding in Industrial Scenarios

Francesco Ragusa, Rosario Leonardi, Michele Mazzamuto +6

Understanding human behavior from complementary egocentric (ego) and exocentric (exo) points of view enables the development of systems that can support workers in industrial envir…

cs.CV2026

GlovEgo-HOI: Bridging the Synthetic-to-Real Gap for Industrial Egocentric Human-Object Interaction Detection

Alfio Spoto, Rosario Leonardi, Francesco Ragusa +1

Egocentric Human-Object Interaction (EHOI) analysis is crucial for industrial safety, yet the development of robust models is hindered by the scarcity of annotated domain-specific…

cs.CV2025

SignIT: A Comprehensive Dataset and Multimodal Analysis for Italian Sign Language Recognition

Alessia Micieli, Giovanni Maria Farinella, Francesco Ragusa

In this work we present SignIT, a new dataset to study the task of Italian Sign Language (LIS) recognition. The dataset is composed of 644 videos covering 3.33 hours. We manually a…