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cs.CV2024
Topological Symmetry Enhanced Graph Convolution for Skeleton-Based Action Recognition
Zeyu Liang, Hailun Xia, Naichuan Zheng +1
Skeleton-based action recognition has achieved remarkable performance with the development of graph convolutional networks (GCNs). However, most of these methods tend to construct…
cs.CV2024★ 3 cited
Signal-SGN: A Spiking Graph Convolutional Network for Skeletal Action Recognition via Learning Temporal-Frequency Dynamics
Naichuan Zheng, Yuchen Du, Hailun Xia +1
For multimodal skeleton-based action recognition, Graph Convolutional Networks (GCNs) are effective models. Still, their reliance on floating-point computations leads to high energ…
cs.CV2024★ 3 cited
MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognition
Naichuan Zheng, Hailun Xia, Zeyu Liang +1
In recent years, multimodal Graph Convolutional Networks (GCNs) have achieved remarkable performance in skeleton-based action recognition. The reliance on high-energy-consuming con…