activity
20192026
most citedQuantitative analysis of robot gesticulation behavior

9 citations · 9 across the 4 of their papers we have counts for

collaborators

5 papers

cs.GR2026

StayStill: a large-scale 3D idle animation dataset

Eneko Atxa Landa, Igor Rodriguez, Elena Lazkano +1

Idle animations are essential for virtual characters, as they convey realistic behaviour during inactive states. While automatic animation generation has been widely studied, limit…

cs.HC2025

Evaluating Idle Animation Believability: a User Perspective

Eneko Atxa Landa, Elena Lazkano, Igor Rodriguez +2

Animating realistic avatars requires using high quality animations for every possible state the avatar can be in. This includes actions like walking or running, but also subtle mov…

cs.CV2025

CapStARE: Capsule-based Sequential Architecture for Robust and Efficient Gaze Estimation

Miren Samaniego, Igor Rodriguez, Elena Lazkano

Human gaze estimation is essential for applications such as human-computer interaction, social robotics, and assistive systems. However, achieving accurate, interpretable, and real…

cs.RO2020★ 9 cited

Quantitative analysis of robot gesticulation behavior

Unai Zabala, Igor Rodriguez, José María Martínez-Otzeta +2

Social robot capabilities, such as talking gestures, are best produced using data driven approaches to avoid being repetitive and to show trustworthiness. However, there is a lack…

cs.RO2019

Learning to gesticulate by observation using a deep generative approach

Unai Zabala, Igor Rodriguez, José María Martínez-Otzeta +1

The goal of the system presented in this paper is to develop a natural talking gesture generation behavior for a humanoid robot, by feeding a Generative Adversarial Network (GAN) w…