This is a list of the SOTA methods for depth estimation. The data are from Deep learning-based monocular depth estimation methods--a state-of-the-art review.
| Name | First Author | AbsRel | SqRel | RMSE | RMSE log | d=1.25 | d=1.25sq | d=1.25cb | Paper | Conf. & Year |
|---|---|---|---|---|---|---|---|---|---|---|
| BTS | Guizilini | 0.060 | 0.182 | 2.005 | 0.092 | 0.959 | 0.994 | 0.999 | 3D packing for self-supervised monocular depth estimation | arXiv 1905.02693 |
| DORN | Fu | 0.071 | 0.268 | 2.271 | 0.116 | 0.936 | 0.985 | 0.995 | Deep ordinal regression network for monocular depth estimation | CVPR 2018 |