Multi Person Pose Estimation On Waf
Métriques
AOP
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | AOP | Paper Title | Repository |
|---|---|---|---|
| DeeperCut | 88.1% | DeeperCut: A Deeper, Stronger, and Faster Multi-Person Pose Estimation Model | |
| Generative Partition Networks | - | Generative Partition Networks for Multi-Person Pose Estimation | |
| DeepCut | 86.5% | DeepCut: Joint Subset Partition and Labeling for Multi Person Pose Estimation |
0 of 3 row(s) selected.