Camera Pose Estimation On Kitti Odometry
Métriques
Absolute Trajectory Error [m]
Average Rotational Error er[%]
Average Translational Error et[%]
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | Absolute Trajectory Error [m] | Average Rotational Error er[%] | Average Translational Error et[%] |
|---|---|---|---|
| digging-into-self-supervised-monocular-depth | 93.04 | 20.72 | 43.21 |
| unsupervised-scale-consistent-depth-and-ego | 37.61 | 5.11 | 12.20 |
| geonet-unsupervised-learning-of-dense-depth | 100.75 | 9.40 | 26.31 |
| scipad-incorporating-spatial-clues-into | 20.83 | 3.17 | 8.63 |
| mgdepth-motion-guided-cost-volume-for-self | - | 2.205 | 7.15 |
| beyond-photometric-loss-for-self-supervised | 25.76 | 4.85 | 11.05 |
| unsupervised-learning-of-depth-and-ego-motion-1 | 72.57 | 12.26 | 29.78 |