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 …

Joint relation modeling is a curial component in human motion prediction. Most existing
methods rely on skeletal-based graphs to build the joint relations, where local interactive …

Intelligent devices, which significantly improve the quality of life and work efficiency, are now
widely integrated into people's daily lives and work. A precise understanding and analysis of …

Human motion prediction from its historical poses is an essential task in computer vision; it is
successfully applied for human-machine interaction and intelligent driving. Recently …

Recurrent neural network (RNN) has become popular for human motion prediction thanks to
its ability to capture temporal dependencies. However, it has limited capacity in modeling the …

Human motion prediction is an increasingly interesting topic in computer vision and robotics.
In this paper, we propose a new end-to-end feedforward network, TrajectoryCNN, to predict …

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 …

Human motion prediction, which aims at predicting future human skeletons given the past
ones, is a typical sequence-to-sequence problem. Therefore, extensive efforts have been …

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

This paper presents a high-quality human motion prediction method that accurately predicts
future human poses given observed ones. Our method is based on the observation that a …