Search Results for author:
Found 2 papers, 1 papers with code
Topological Symmetry Enhanced Graph Convolution for Skeleton-Based Action Recognition
However, most of these methods tend to construct complex topology learning mechanisms while neglecting the inherent symmetry of the human body.
MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition
We propose an innovative Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation (MK-SGN) to address this issue.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
