3D Multi Person Pose Estimation Absolute On
Métriques
3DPCK
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | 3DPCK |
|---|---|
| monocular-3d-multi-person-pose-estimation-by | 48.0 |
| multi-person-absolute-3d-human-pose | 37.3 |
| permutation-invariant-relational-network-for | 44.1 |
| graph-and-temporal-convolutional-networks-for | 45.7 |
| hmor-hierarchical-multi-person-ordinal | 43.8 |
| dynamic-graph-reasoning-for-multi-person-3d | 41.2 |
| explicit-occlusion-reasoning-for-multi-person | 36.5 |
| absolute-human-pose-estimation-with-depth | - |
| hdnet-human-depth-estimation-for-multi-person | 35.2 |
| virtualpose-learning-generalizable-3d-human | 44 |
| camera-distance-aware-top-down-approach-for | 31.5 |
| smap-single-shot-multi-person-absolute-3d | 35.4 |
| towards-robust-and-smooth-3d-multi-person | 50.9 |
| distribution-aware-single-stage-models-for | 39.2 |