Depth Estimation on Make3D (test)
2.277C1 RMSEOurs (direct optimization approach)
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Ours (direct optimization approach)Learning Paradigm=Analytical2026.02 | 2.277 | 0.0663 | 5.63 | 0.0695 | |
| Fu et al. (DORN)Learning Paradigm=Supervised learning2026.02 | 3.97 | 0.157 | 7.32 | 0.162 | |
| Nazir et al.Learning Paradigm=Supervised learning2026.02 | 4.178 | 0.153 | 6.132 | 0.17 | |
| Xu et al. (MS-CRF)Learning Paradigm=Supervised learning2026.02 | 4.38 | 0.184 | 8.56 | 0.198 | |
| Li et al.Learning Paradigm=Supervised learning2026.02 | 7.12 | 0.278 | 10.27 | 0.279 | |
| Gur & WolfLearning Paradigm=Self-supervised learning, Input Modality=All-in-focus (AIF), Focal stack settings=F6, rendered focal stack with six focus settings2026.02 | 7.474 | 0.262 | 9.248 | 0.269 | |
| Wang et al.Learning Paradigm=Self-supervised learning, Input Modality=stereo/monocular video2026.02 | 8.09 | 0.387 | — | — | |
| Zhou et al.Learning Paradigm=Self-supervised learning, Input Modality=stereo/monocular video2026.02 | 10.47 | 0.383 | — | — | |
| Godard et al.Learning Paradigm=Self-supervised learning, Input Modality=stereo/monocular video2026.02 | 11.513 | 0.443 | — | — |