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Found 14 papers, 9 papers with code
Learning to Detect Attended Objects in Cultural Sites with Gaze Signals and Weak Object Supervision
To study the problem, we collect a dataset of egocentric images collected by subjects visiting a museum.
World-Map Misalignment Detection for Visual Navigation Systems
While the results are promising, we also note that the proposed problem is challenging, due to the domain shift between synthetic and real data, and the difficulty in acquiring real data.
Are Synthetic Data Useful for Egocentric Hand-Object Interaction Detection?
In this study, we investigate the effectiveness of synthetic data in enhancing egocentric hand-object interaction detection.
Ego-Exo4D: Understanding Skilled Human Activity from First- and Third-Person Perspectives
We present Ego-Exo4D, a diverse, large-scale multimodal multiview video dataset and benchmark challenge.
ENIGMA-51: Towards a Fine-Grained Understanding of Human-Object Interactions in Industrial Scenarios
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 (e. g., electric screwdriver) and equipments (e. g., oscilloscope).
Exploiting Multimodal Synthetic Data for Egocentric Human-Object Interaction Detection in an Industrial Scenario
In this paper, we tackle the problem of Egocentric Human-Object Interaction (EHOI) detection in an industrial setting.
StillFast: An End-to-End Approach for Short-Term Object Interaction Anticipation
Anticipation problem has been studied considering different aspects such as predicting humans' locations, predicting hands and objects trajectories, and forecasting actions and human-object interactions.
MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain
To encourage research in this field, we present MECCANO, a multimodal dataset of egocentric videos to study humans behavior understanding in industrial-like settings.
Egocentric Human-Object Interaction Detection Exploiting Synthetic Data
We consider the problem of detecting Egocentric HumanObject Interactions (EHOIs) in industrial contexts.
Weakly Supervised Attended Object Detection Using Gaze Data as Annotations
Since labeling large amounts of data to train a standard object detector is expensive in terms of costs and time, we propose a weakly supervised version of the task which leans only on gaze data and a frame-level label indicating the class of the attended object.
The MECCANO Dataset: Understanding Human-Object Interactions from Egocentric Videos in an Industrial-like Domain
To fill this gap, we introduce MECCANO, the first dataset of egocentric videos to study human-object interactions in industrial-like settings.
Ranked #1 on
Action Recognition
on MECCANO
EGO-CH: Dataset and Fundamental Tasks for Visitors BehavioralUnderstanding using Egocentric Vision
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 goods with augmented reality.
Egocentric Visitors Localization in Cultural Sites
We consider the problem of localizing visitors in a cultural site from egocentric (first person) images.
