Orientation Estimation on ITODD SiSo
2.8ARCSARR–Gray
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| SARR–GrayTraining=RGB2Gray: S, Test=Gray, Scope=dataset, Model=✗, Symmetry=representation2026.04 | 2.8 | 6.9 | 0.073 | |
| SARR–GrayTraining=RGB2Gray: S, Test=Gray, Scope=dataset*, Model=✗, Symmetry=representation2026.04 | 6.5 | 22.5 | 0.082 | |
| SARR–GrayTraining=RGB2Gray: S, Test=Gray, Scope=symmetry, Model=✗, Symmetry=representation2026.04 | 7.1 | 24 | 0.088 | |
| SARR–GrayTraining=RGB2Gray: S, Test=Gray, Scope=object, Model=✗, Symmetry=representation2026.04 | 10.8 | 23.6 | 0.08 | |
| Cai et al. (2022)Training=RGB: S, Test=RGB, Scope=dataset, Model=✗, Symmetry=network2026.04 | 36.7 | 74 | 0.053 | |
| SARR–DepthTraining=D: S, Test=D, Scope=object, Model=✗, Symmetry=representation2026.04 | 38.3 | 62.1 | 0.071 | |
| SARR–DepthTraining=D: S, Test=D, Scope=symmetry, Model=✗, Symmetry=representation2026.04 | 41 | 68.7 | 0.079 | |
| SARR–DepthTraining=D: S, Test=D, Scope=dataset, Model=✗, Symmetry=representation2026.04 | 41 | 63.7 | 0.066 | |
| SARR–DepthTraining=D: S, Test=D, Scope=dataset*, Model=✗, Symmetry=representation2026.04 | 44.8 | 56.3 | 0.078 |