Skeleton Based Action Recognition On Ut
المقاييس
Accuracy
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
| Paper Title | ||
|---|---|---|
| Temporal Subspace Clustering | 99.50% | Subspace Clustering for Action Recognition with Covariance Representations and Temporal Pruning |
| SCK⊕+DCK⊕ | 99.2 | Tensor Representations for Action Recognition |
| Complete GR-GCN | 98.5% | Optimized Skeleton-based Action Recognition via Sparsified Graph Regression |
| DPRL | 98.5% | Deep Progressive Reinforcement Learning for Skeleton-Based Action Recognition |
| SCK+DCK | 98.2 | Tensor Representations for Action Recognition |
| Lie Group | 97.1% | Human Action Recognition by Representing 3D Skeletons as Points in a Lie Group |
| GFT | 96% | Graph Based Skeleton Modeling for Human Activity Analysis |
0 of 7 row(s) selected.