Monocular Depth Estimation On Make3D
Métriques
Abs Rel
RMSE
Sq Rel
Résultats
Résultats de performance de divers modèles sur ce benchmark
Nom du modèle | Abs Rel | RMSE | Sq Rel | Paper Title | Repository |
|---|---|---|---|---|---|
| GCNDepth | 0.424 | 6.757 | 3.075 | GCNDepth: Self-supervised Monocular Depth Estimation based on Graph Convolutional Network | - |
| AnyNet [88] | - | 0.232 | - | A Survey on Deep Learning Techniques for Stereo-based Depth Estimation | - |
| SharinGAN | 0.377 | 8.388 | 4.9 | SharinGAN: Combining Synthetic and Real Data for Unsupervised Geometry Estimation | - |
| HighResNet [32] | - | 0.474 | - | A Survey on Deep Learning Techniques for Stereo-based Depth Estimation | - |
| SPIDepth | 0.299 | 6.672 | 1.931 | SPIdepth: Strengthened Pose Information for Self-supervised Monocular Depth Estimation | - |
| Monodepth2 | 0.322 | 7.417 | 3.589 | Digging Into Self-Supervised Monocular Depth Estimation | - |
0 of 6 row(s) selected.