Hand Pose Estimation On Icvl Hands
Métriques
Average 3D Error
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Average 3D Error |
|---|---|
| dense-3d-regression-for-hand-pose-estimation | 7.3 |
| efficient-virtual-view-selection-for-3d-hand | 4.79 |
| v2v-posenet-voxel-to-voxel-prediction-network | 6.28 |
| shpr-net-deep-semantic-hand-pose-regression | 7.22 |
| pushing-the-envelope-for-depth-based-semi | 5.99 |
| a2j-anchor-to-joint-regression-network-for-3d | 6.461 |
| towards-good-practices-for-deep-3d-hand-pose | 7.31 |
| trihorn-net-a-model-for-accurate-depth-based | 5.73 |
| handfoldingnet-a-3d-hand-pose-estimation | 5.95 |
| awr-adaptive-weighting-regression-for-3d-hand | 5.98 |
| deepprior-improving-fast-and-accurate-3d-hand | 8.1 |
| region-ensemble-network-improving | 7.5 |
| mutr-multi-stage-transformer-for-hand-pose | 5.98 |
| pixel-wise-regression-3d-hand-pose-estimation | 6.152 |
| pose-guided-structured-region-ensemble | 6.8 |