3D Multi Person Pose Estimation Root Relative
Metrics
3DPCK
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | 3DPCK |
|---|---|
| distribution-aware-single-stage-models-for | 82.7 |
| towards-robust-and-smooth-3d-multi-person | 83.7 |
| dynamic-graph-reasoning-for-multi-person-3d | 84.6 |
| single-shot-multi-person-3d-pose-estimation | 65 |
| smap-single-shot-multi-person-absolute-3d | 73.5 |
| pi-net-pose-interacting-network-for-multi | 82.5 |
| explicit-occlusion-reasoning-for-multi-person | 79.4 |
| hmor-hierarchical-multi-person-ordinal | 82.0 |
| lcr-net-localization-classification | - |
| camera-distance-aware-top-down-approach-for | 81.8 |
| single-shot-multi-person-3d-pose-estimation | - |
| temporal-smoothing-for-3d-human-pose | 85.3 |
| multi-person-absolute-3d-human-pose | 82.7 |
| monocular-3d-multi-person-pose-estimation-by | 89.6 |
| deep-monocular-3d-human-pose-estimation-via | 83.3 |
| permutation-invariant-relational-network-for | 85.8 |
| dual-networks-based-3d-multi-person-pose | 89.6 |
| graph-and-temporal-convolutional-networks-for | 87.5 |
| absolute-human-pose-estimation-with-depth | - |
| hdnet-human-depth-estimation-for-multi-person | 83.7 |