DG-STA builds dynamic graphs from hand skeletons, applies spatial-temporal self-attention to learn features, and uses a mask to cut cost by 99%, outperforming prior methods on DHG-14/28 and SHREC'17.
Quantized densely connected U-Nets for efficient landmark localization
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Construct Dynamic Graphs for Hand Gesture Recognition via Spatial-Temporal Attention
DG-STA builds dynamic graphs from hand skeletons, applies spatial-temporal self-attention to learn features, and uses a mask to cut cost by 99%, outperforming prior methods on DHG-14/28 and SHREC'17.