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SOTA
Skelettbasierte Aktionserkennung
Skeleton Based Action Recognition On Sysu 3D
Skeleton Based Action Recognition On Sysu 3D
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Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Accuracy
Paper Title
SGN
86.9%
Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition
VA-fusion (aug.)
86.7%
View Adaptive Neural Networks for High Performance Skeleton-based Human Action Recognition
EleAtt-GRU (aug.)
85.7%
EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks
Local+LGN
83.14%
Learning Latent Global Network for Skeleton-based Action Prediction
Complete GR-GCN
77.9%
Optimized Skeleton-based Action Recognition via Sparsified Graph Regression
VA-LSTM
77.5%
View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data
DPRL
76.9%
Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition
Dynamic Skeletons
75.5%
Jointly learning heterogeneous features for rgb-d activity recognition
ST-LSTM (Tree)
73.4%
Skeleton-Based Action Recognition Using Spatio-Temporal LSTM Network with Trust Gates
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Skeleton Based Action Recognition On Sysu 3D | SOTA | HyperAI