Skeleton Based Action Recognition On Sbu
Métriques
Accuracy
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Accuracy |
|---|---|
| mlgcn-multi-laplacian-graph-convolutional | 98.60% |
| graph-neural-networks-with-convolutional-arma | 96.00% |
| view-adaptive-neural-networks-for-high | 98.3% |
| real-time-hand-gesture-recognition | 93.96 |
| on-geometric-features-for-skeleton-based | 99.02% |
| deepgru-deep-gesture-recognition-utility | 95.7% |
| convolutional-neural-networks-on-graphs-with | 96.00% |
| spatio-temporal-lstm-with-trust-gates-for-3d | 93.3% |
| simplifying-graph-convolutional-networks | 94.0% |