Taskonomy
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Depth Estimation | Taskonomy (test) | Depth Estimation Error0.022 | 21 | |
| Depth Estimation | Taskonomy | Depth Error0.1054 | 18 | |
| Keypoint Detection | Taskonomy tiny (test) | MAE0.191 | 16 | |
| Semantic Segmentation | Taskonomy tiny (test) | mIoU73.7 | 16 | |
| Semantic Segmentation | Taskonomy (test) | mIoU73.7 | 16 | |
| Scene Classification | Taskonomy (val) | Model Loss1.3 | 15 | |
| Euclidean Depth Estimation | Taskonomy (val) | Model Loss0.058 | 15 | |
| 3D Keypoints | Taskonomy (val) | Model Loss0.069 | 15 | |
| Semantic Segmentation | Taskonomy (val) | Model Loss0.034 | 15 | |
| Surface Normals | Taskonomy (val) | Model Loss0.159 | 15 | |
| Reshading | Taskonomy (val) | Model Loss0.035 | 15 | |
| 2D Edges | Taskonomy (val) | Model Loss0.054 | 15 | |
| Multi-task Dense Prediction | Taskonomy (test) | DE (L1)0.016 | 13 | |
| Edge Detection | Taskonomy (test) | Edge Det.21.7 | 10 | |
| Keypoint Detection | Taskonomy (test) | Keypoint Detection20.2 | 10 | |
| Surface Normal Prediction | Taskonomy (test) | Surface Normal Accuracy87.3 | 10 | |
| Keypoint-3D Detection | Taskonomy | K.-3D Score43.47 | 9 | |
| Curvatures | Taskonomy | Curvature1.3501 | 9 | |
| Edge-3D Detection | Taskonomy | E.-3D Score55.25 | 9 | |
| Keypoint-2D Detection | Taskonomy | K.-2D Score54.81 | 9 | |
| Reshading | Taskonomy | Residual Score0.1487 | 9 | |
| Edge-2D Detection | Taskonomy | E-2D Score18.46 | 9 | |
| Semantic Segmentation | Taskonomy | Segmentation Score72.82 | 9 | |
| Edge Detection | Taskonomy | MAE0.046 | 9 | |
| Surface Normal Estimation | Taskonomy | CS0.931 | 9 |
Showing 25 of 63 rows