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An End-to-End Spatio-Temporal Attention Model for Human Action Recognition from Skeleton Data

AAAI 2017 · Video › Action recognition · approach: Skeleton-based action recognition · 862 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
add spatial and temporal attentionLSTM · SBUaccuracy (%): 86.72 -> 91.51Helped
add spatial attention (ablation)LSTM · NTU Cross-Subjectaccuracy (%): 66.80 -> 71.89Helped
add temporal attention (ablation)LSTM · NTU Cross-Subjectaccuracy (%): 66.80 -> 73.16Helped
add spatial and temporal attentionLSTM · NTU Cross-Subjectaccuracy (%): 66.80 -> 73.42Helped
add spatial attention (ablation)LSTM · NTU Cross-Viewaccuracy (%): 77.53 -> 80.35Helped
add temporal attention (ablation)LSTM · NTU Cross-Viewaccuracy (%): 77.53 -> 80.51Helped
add spatial and temporal attentionLSTM · NTU Cross-Viewaccuracy (%): 77.53 -> 81.23Helped
add spatial attention regularization (ablation)SA-LSTM · SBU, NTU Cross-Subject, NTU Cross-ViewaccuracyHelped
add temporal attention regularization (ablation)TA-LSTM · SBU, NTU Cross-Subject, NTU Cross-ViewaccuracyHelped
add spatial attention (ablation)LSTM · SBUaccuracy (%): 86.72 -> 88.00Helped
add temporal attention (ablation)LSTM · SBUaccuracy (%): 86.72 -> 88.79Helped

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