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Keypoint Detection On Coco Test Challenge
Métriques
AR
ARM
Résultats
Résultats de performance de divers modèles sur ce benchmark
| Paper Title | |||
|---|---|---|---|
| 4×RSN-50 | 82.6 | 78.0 | Learning Delicate Local Representations for Multi-Person Pose Estimation |
| MSPN+* | 82.2 | 77.5 | Rethinking on Multi-Stage Networks for Human Pose Estimation |
| Simple Base+* | 80.5 | 75.3 | Simple Baselines for Human Pose Estimation and Tracking |
| CPN+ | 78.7 | 74.3 | Cascaded Pyramid Network for Multi-Person Pose Estimation |
| Mask R-CNN* | 75.4 | 70.2 | Mask R-CNN |
| G-RMI* | 75.1 | 69.7 | Towards Accurate Multi-person Pose Estimation in the Wild |
| Girdhar et al. | 70.2 | 60.7 | Detect-and-Track: Efficient Pose Estimation in Videos |
| Xiu et al. | 67.5 | 62.5 | Pose Flow: Efficient Online Pose Tracking |
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