Body part-based dual-task spatio-temporal graph convolutional network for action quality assessment

BPA-STGCN: Body-Part-Aware Spatio-Temporal Graph Convolutional Network for Stable Skeleton-Based Action Recognition

Comprehensive ablation studies reveal that the architectural innovations and the stability protocol contribute complementarily, and that BPA-STGCN achieves the best accuracy–stability trade-off among all tested configurations.

Spatio-temporal local graph convolutional network for skeleton-based action recognition

A novel approach called Spatio-Temporal Local Graph Convolutional Network, which consists of a Partitioning Module (PM), a Spatio-Temporal Graph Convolution (ST-GC) module and a Joint Prototype Loss (JPL) function, which facilitates the capture of local relationships between joints.

SAT-GCN: Spatial-Aware Transformer-Enhanced Graph Convolutional Network for Skeleton-Based Action Recognition

Research on Rehabilitation Training Movement Recognition and Real-time Feedback Model Based on Computer Vision

This study provides a replicable technical path for the validation of rehabilitation evaluation algorithms without clinical data collection through the adaptive fusion mechanism to dynamically integrate the confidence of the deep network and the matching score of dynamic time warping template.

Motion-Aware Graph Convolutional Network for Topology-Enhanced Skeleton-Based Action Recognition

Skeleton-based action recognition has achieved significant progress through spatio-temporal graph convolutional networks. However, existing topology-enhanced methods treat all skeletal joints uniformly, failing to emphasize task-relevant joints for coordination-level hand-centric actions. Moreover, the graph topology i...

NeuroPath: Brain-inspired dual-pathway Graph Convolutional Networks for skeleton-based action recognition

Skeleton-based action recognition aims to recognize human actions from sequences of human joint coordinates. Most existing Spatial-Temporal Graph Convolutional Networks (STGCNs) have achieved promising results by modeling skeletal structures with implicit spatial-temporal representations. However, our empirical study r...