HUI360 : A 360° Egocentric Dataset and Baselines for Human-Robot Interaction Anticipation

Raphael Lorenzo-Louis; Fabio Amadio; Bertrand Luvison; Serena Ivaldi

doi:10.1109/fg67764.2026.11556969

May 25, 2026Open Access

HUI360 : A 360° Egocentric Dataset and Baselines for Human-Robot Interaction Anticipation

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Key Points

The aim is to create a comprehensive dataset that supports the anticipation of robot behavior during interactions with humans.
Development of the HUI360 360° egocentric dataset for capturing human-robot interactions.
Establishment of baselines to evaluate anticipation algorithms in human-robot scenarios.
The dataset provides a rich source of data for training anticipation models.
Baseline performance metrics on the dataset demonstrate the potential for enhanced predictive capabilities in human-robot interactions.

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Implication

Dataset development demonstrates new baselines for anticipating robot behavior in human-robot interactions, suggesting improved interaction strategies.

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Lorenzo-Louis et al. (2026) studied this question.

synapsesocial.com/papers/6a362e62db0793dc1a536229 https://doi.org/10.1109/fg67764.2026.11556969

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HUI360 : A 360° Egocentric Dataset and Baselines for Human-Robot Interaction Anticipation

Key Points

No abstract yet

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Implication

Abstract

Discussion

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HUI360 : A 360° Egocentric Dataset and Baselines for Human-Robot Interaction Anticipation

Key Points

No abstract yet

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Implication

Abstract

Discussion

Cite This Study

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