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
Nom du modèle | Absolute Trajectory Error [m] | Average Rotational Error er[%] | Average Translational Error et[%] | Paper Title | Repository |
|---|---|---|---|---|---|
| Monodepth2 | 93.04 | 20.72 | 43.21 | Digging Into Self-Supervised Monocular Depth Estimation | - |
| SC-Depth | 37.61 | 5.11 | 12.20 | Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video | - |
| GeoNet | 100.75 | 9.40 | 26.31 | GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose | - |
| SCIPaD | 20.83 | 3.17 | 8.63 | SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning | - |
| Manydepth2 | - | 2.205 | 7.15 | Manydepth2: Motion-Aware Self-Supervised Monocular Depth Estimation in Dynamic Scenes | - |
| DeepMatchVO | 25.76 | 4.85 | 11.05 | Beyond Photometric Loss for Self-Supervised Ego-Motion Estimation | - |
| SfMLearner | 72.57 | 12.26 | 29.78 | Unsupervised Learning of Depth and Ego-Motion from Video | - |
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