Context-based Interpretable Spatio-Temporal Graph Convolutional Network for Human Motion Forecasting

The author presents a Context-based Interpretable Spatio-Temporal Graph Convolutional Network (CIST-GCN) as an efficient 3D human pose forecasting model based on GCNs, aiming to enhance interpretability in motion prediction.