Multi-Scale Spatial-Temporal Self-Attention Graph Convolutional Networks for Skeleton-based Action Recognition

arXiv:2404.02624v1 Announce Type: new
Abstract: Skeleton-based gesture recognition methods have achieved high success using Graph Convolutional Network (GCN). In addition, context-dependent adaptive topology as a neighborhood vertex information and attention mechanism leverages a model to better represent actions. In this paper, we propose self-attention GCN hybrid model, Multi-Scale Spatial-Temporal self-attention (MSST)-GCN to effectively improve modeling ability to achieve state-of-the-art results on several datasets. We utilize spatial self-attention module with adaptive topology to understand intra-frame interactions within a frame among different …

abstract action recognition arxiv attention context cs.cv gesture recognition graph hybrid information network networks paper recognition scale self-attention spatial success temporal topology type vertex