Long-term and accurate forecasting is the long-standing pursuit of the human motion
prediction task. Existing methods typically suffer from dramatic degradation in prediction …

Encouraged by the effectiveness of encoding temporal dynamics within the frequency
domain, recent human motion prediction systems prefer to first convert the motion …

Predicting diverse human motions given a sequence of historical poses has received
increasing attention. Despite rapid progress, existing work captures the multi-modal nature …

Human motion prediction aims to forecast an upcoming pose sequence given a past human
motion trajectory. To address the problem, in this work we propose FreqMRN, a human …

As an important and challenging task in computer vision, human motion prediction aims to
predict the future human motion sequence from a given historical sequence. Though the …

A variety of real-world applications rely on accurate predictions of 3D human motion from
their past observations. While existing methods have made notable progress, their …

Predicting future motion based on historical motion sequence is a fundamental problem in
computer vision, and it has wide applications in autonomous driving and robotics. Some …

The dynamic information of the joints, such as the movement amplitude, is critical for
forecasting precise human joint trajectories. Existing methods adopt global modeling in …

Extrapolating future human motion based on the historical human pose sequence is the
foundation of various intelligent applications. Numerous deep learning-based algorithms …

Despite the great progress in human motion prediction, it remains a challenging task due to
the complicated structural dynamics of human behaviors. In this paper, we address this …