From Sparse Signal to Smooth Motion: Real-Time Motion Generation with Rolling Prediction Models

Germán Barquero; Nadine Bertsch; Manojkumar Marramreddy; Carlos Chacón; Filippo Arcadu; Ferran Rigual; Nicky Sijia He; Cristina Palmero; Sergio Escalera; Yuting Ye; Robin Kips

doi:10.1109/cvpr52734.2025.00179

CVPR2025顶会

From Sparse Signal to Smooth Motion: Real-Time Motion Generation with Rolling Prediction Models

Germán Barquero, Nadine Bertsch, Manojkumar Marramreddy, Carlos Chacón, Filippo Arcadu, Ferran Rigual, Nicky Sijia He, Cristina Palmero, Sergio Escalera, Yuting Ye, Robin Kips

DOI 出版方

2025年份

4顶会引用

摘要

Figure 1. We introduce Rolling Prediction Model, an approach that generates smooth and realistic full-body human motion in the two of the most common XR sensing signals: hand controllers, in which the tracking signal is always available (left), and hand tracking, in which the tracking signal is noisy and might be lost for long periods of time (right). Tracking input trajectories are shown as magenta lines.