39 citations · 64 across the 16 of their papers we have counts for
19 papers
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…
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…
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…
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…
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…
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…
Ego-EXTRA: video-language Egocentric Dataset for EXpert-TRAinee assistance
Francesco Ragusa, Michele Mazzamuto, Rosario Forte +5
We present Ego-EXTRA, a video-language Egocentric Dataset for EXpert-TRAinee assistance. Ego-EXTRA features 50 hours of unscripted egocentric videos of subjects performing procedur…
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…
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
Kristen Grauman, Andrew Westbury, Lorenzo Torresani +98
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge. Ego-Exo4D centers around simultaneously-captured egocentric and exocentric…
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…
An Outlook into the Future of Egocentric Vision
Chiara Plizzari, Gabriele Goletto, Antonino Furnari +5
What will the future be? We wonder! In this survey, we explore the gap between current research in egocentric vision and the ever-anticipated future, where wearable computing, with…
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…
StillFast: An End-to-End Approach for Short-Term Object Interaction Anticipation
Francesco Ragusa, Giovanni Maria Farinella, Antonino Furnari
Anticipation problem has been studied considering different aspects such as predicting humans' locations, predicting hands and objects trajectories, and forecasting actions and hum…
MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain
Francesco Ragusa, Antonino Furnari, Giovanni Maria Farinella
Wearable cameras allow to acquire images and videos from the user's perspective. These data can be processed to understand humans behavior. Despite human behavior analysis has been…
Weakly Supervised Attended Object Detection Using Gaze Data as Annotations
Michele Mazzamuto, Francesco Ragusa, Antonino Furnari +2
We consider the problem of detecting and recognizing the objects observed by visitors (i.e., attended objects) in cultural sites from egocentric vision. A standard approach to the…
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,…
The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain
Francesco Ragusa, Antonino Furnari, Salvatore Livatino +1
Wearable cameras allow to collect images and videos of humans interacting with the world. While human-object interactions have been thoroughly investigated in third person vision,…
EGO-CH: Dataset and Fundamental Tasks for Visitors BehavioralUnderstanding using Egocentric Vision
Francesco Ragusa, Antonino Furnari, Sebastiano Battiato +2
Equipping visitors of a cultural site with a wearable device allows to easily collect information about their preferences which can be exploited to improve the fruition of cultural…
Egocentric Visitors Localization in Cultural Sites
Francesco Ragusa, Antonino Furnari, Sebastiano Battiato +2
We consider the problem of localizing visitors in a cultural site from egocentric (first person) images. Localization information can be useful both to assist the user during his v…