Guided Depth Super-Resolution on Lu
0.8RMSE (x4)SSDNet 2023
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| SSDNet 2023Training Dataset=NYU v22026.04 | 0.8 | 1.82 | 4.77 | |
| FDKN 2021Training Dataset=NYU v22026.04 | 0.82 | 2.1 | 5.05 | |
| DAGF 2023Training Dataset=NYU v22026.04 | 0.83 | 1.93 | 4.8 | |
| NAIMATraining Dataset=NYU v22026.04 | 0.84 | 1.44 | 3.34 | |
| JIIF 2021Training Dataset=NYU v22026.04 | 0.85 | 1.73 | 4.16 | |
| DCTNet 2022Training Dataset=NYU v22026.04 | 0.88 | 1.85 | 4.39 | |
| DKN 2021Training Dataset=NYU v22026.04 | 0.96 | 2.16 | 5.11 | |
| DADA 2023Training Dataset=NYU v22026.04 | 0.96 | 1.87 | 4.01 | |
| SGNet 2024Training Dataset=NYU v22026.04 | 1.03 | 1.61 | 3.55 | |
| SUFT 2022Training Dataset=NYU v22026.04 | 1.1 | 1.74 | 3.92 | |
| FDSR 2021Training Dataset=NYU v22026.04 | 1.29 | 2.19 | 5 |