Multi Person Pose Estimation On Waf
Metrics
AOP
Results
Performance results of various models on this benchmark
Model Name | 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 |
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