activity
20222026
most citedThe Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized

16 citations · 19 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2026★ 3 cited

Context-free Self-Conditioned GAN for Trajectory Forecasting

Tiago Rodrigues de Almeida, Eduardo Gutierrez Maestro, Oscar Martinez Mozos

In this paper, we present a context-free unsupervised approach based on a self-conditioned GAN to learn different modes from 2D trajectories. Our intuition is that each mode indica…

cs.RO2024

THÖR-MAGNI Act: Actions for Human Motion Modeling in Robot-Shared Industrial Spaces

Tiago Rodrigues de Almeida, Tim Schreiter, Andrey Rudenko +3

Accurate human activity and trajectory prediction are crucial for ensuring safe and reliable human-robot interactions in dynamic environments, such as industrial settings, with mob…

cs.RO2024

THÖR-MAGNI: A Large-scale Indoor Motion Capture Recording of Human Movement and Robot Interaction

Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu +7

We present a new large dataset of indoor human and robot navigation and interaction, called THÖR-MAGNI, that is designed to facilitate research on social navigation: e.g., modellin…

cs.LG2023

Likely, Light, and Accurate Context-Free Clusters-based Trajectory Prediction

Tiago Rodrigues de Almeida, Oscar Martinez Mozos

Autonomous systems in the road transportation network require intelligent mechanisms that cope with uncertainty to foresee the future. In this paper, we propose a multi-stage proba…

cs.RO2022★ 16 cited

The Magni Human Motion Dataset: Accurate, Complex, Multi-Modal, Natural, Semantically-Rich and Contextualized

Tim Schreiter, Tiago Rodrigues de Almeida, Yufei Zhu +9

Rapid development of social robots stimulates active research in human motion modeling, interpretation and prediction, proactive collision avoidance, human-robot interaction and co…