Skeleton Based Action Recognition On H2O 2

Accuracy

Results

Performance results of various models on this benchmark

		Paper Title
CHASE(STSA-Net)	94.77	CHASE: Learning Convex Hull Adaptive Shift for Skeleton-based Multi-Entity Action Recognition
SHARP	91.73	SHARP: Segmentation of Hands and Arms by Range using Pseudo-Depth for Enhanced Egocentric 3D Hand Pose Estimation and Action Recognition
EffHandEgoNet	91.32	In My Perspective, In My Hands: Accurate Egocentric 2D Hand Pose and Action Recognition
ISTA-Net	89.09±1.21	Interactive Spatiotemporal Token Attention Network for Skeleton-based General Interactive Action Recognition

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