Recent advances in deterministic human motion prediction: A review

T Deng, Y Sun - Image and Vision Computing, 2024 - Elsevier
In recent years, the rapid advancement of deep learning and the advent of extensive human
motion datasets have significantly enhanced the prominence of human motion prediction …

AMHGCN: Adaptive multi-level hypergraph convolution network for human motion prediction

J Li, J Wang, L Wu, X Wang, X Luo, Y Xu - Neural Networks, 2024 - Elsevier
Human motion prediction is the key technology for many real-life applications, eg, self-
driving and human–robot interaction. The recent approaches adopt the unrestricted full …

A human-like action learning process: Progressive pose generation for motion prediction

J Li, J Wang, C Kuang, L Wu, X Wang, Y Xu - Knowledge-Based Systems, 2023 - Elsevier
Human motion prediction is crucial for the human–robot inter-action and self-driving. We
human beings learn an action with two stages, ie, the approximation stage and the …

Spatiotemporal consistency learning from momentum cues for human motion prediction

H Chen, J Hu, W Zhang, P Su - IEEE Transactions on Circuits …, 2023 - ieeexplore.ieee.org
Extrapolating future human motion based on the historical human pose sequence is the
foundation of various intelligent applications. Numerous deep learning-based algorithms …

Simplified neural architecture for efficient human motion prediction in human-robot interaction

J Zou - Neurocomputing, 2024 - Elsevier
Human motion prediction is essential for safe and effective human-robot interaction, but
modeling the intricate spatio-temporal dynamics inherent in human movement remains …

Human Motion Prediction: Assessing Direct and Geometry-Aware Approaches in 3D Space

S Idrees, J Kim, J Choi, S Sohn - IEEE Access, 2024 - ieeexplore.ieee.org
Predicting 3D human motion is a complex task, owing to the unpredictable nature of human
movements. The influx of deep learning innovations and the availability of extensive …