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20222026
most citedExploiting Multimodal Synthetic Data for Egocentric Human-Object Interaction Detection in an Industrial Scenario

3 citations · 3 across the 10 of their papers we have counts for

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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 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

Learning Egocentric In-Hand Object Segmentation through Weak Supervision from Human Narrations

Nicola Messina, Rosario Leonardi, Luca Ciampi +4

Pixel-level recognition of objects manipulated by the user from egocentric images enables key applications spanning assistive technologies, industrial safety, and activity monitori…

cs.CV2025

A Real-Time System for Egocentric Hand-Object Interaction Detection in Industrial Domains

Antonio Finocchiaro, Alessandro Sebastiano Catinello, Michele Mazzamuto +3

Hand-object interaction detection remains an open challenge in real-time applications, where intuitive user experiences depend on fast and accurate detection of interactions with s…

cs.CV2023

Are Synthetic Data Useful for Egocentric Hand-Object Interaction Detection?

Rosario Leonardi, Antonino Furnari, Francesco Ragusa +1

In this study, we investigate the effectiveness of synthetic data in enhancing egocentric hand-object interaction detection. Via extensive experiments and comparative analyses on t…

cs.CV2023

ENIGMA-51: Towards a Fine-Grained Understanding of Human-Object Interactions in Industrial Scenarios

Francesco Ragusa, Rosario Leonardi, Michele Mazzamuto +4

ENIGMA-51 is a new egocentric dataset acquired in an industrial scenario by 19 subjects who followed instructions to complete the repair of electrical boards using industrial tools…

cs.CV2023★ 3 cited

Exploiting Multimodal Synthetic Data for Egocentric Human-Object Interaction Detection in an Industrial Scenario

Rosario Leonardi, Francesco Ragusa, Antonino Furnari +1

In this paper, we tackle the problem of Egocentric Human-Object Interaction (EHOI) detection in an industrial setting. To overcome the lack of public datasets in this context, we p…

cs.CV2022

Egocentric Human-Object Interaction Detection Exploiting Synthetic Data

Rosario Leonardi, Francesco Ragusa, Antonino Furnari +1

We consider the problem of detecting Egocentric HumanObject Interactions (EHOIs) in industrial contexts. Since collecting and labeling large amounts of real images is challenging,…