Semantic Segmentation on NYUv2 13-class
78.3AccuracySemAffiNet
Evaluation results
| Method | Links | |||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SemAffiNet2022.05 | 78.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BPNet2021.03 | 73.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| BPNet2022.05 | 73.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 3DMV2021.03 | 71.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 3DMV2022.05 | 71.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Dai et al.Task Type=11-class2021.03 | 60.7 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SemanticFusion2021.03 | 59.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SemanticFusion2022.05 | 59.2 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Hermans et al.2021.03 | 54.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| Hermans et al.2022.05 | 54.3 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SceneNet2021.03 | 52.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| SceneNet2022.05 | 52.5 | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | — | |
| 3D-FCNN-TIinitialization=10 different random initializations2017.10 | — | 69.3 | 40.26 | 64.34 | 64.41 | 73.05 | 95.55 | 21.15 | 55.51 | 45.09 | 84.96 | 20.76 | 42.24 | 23.95 | 42.13 | 53.9 | 67.38 | |
| Couprie et al.2017.10 | — | 38.1 | 8.7 | 34.1 | 42.4 | 62.6 | 87.3 | 40.4 | 24.6 | 10.2 | 86.1 | 15.9 | 13.7 | 6 | — | 36.2 | 52.4 | |
| Hermans et al.2017.10 | — | 68.4 | 8.6 | 41.9 | 37.1 | 83.4 | 91.5 | 35.8 | 28.5 | 27.7 | 71.8 | 46.1 | 45.4 | 38.4 | — | 48 | 54.2 | |
| SEGCloudcomponents=3D-FCNN-TI + CRF, initialization=10 different random initializations2017.10 | — | 75.06 | 39.28 | 62.92 | 61.8 | 69.16 | 95.21 | 34.38 | 62.78 | 45.78 | 78.89 | 26.35 | 53.46 | 28.5 | 43.45 | 56.43 | 66.82 | |
| Wang et al.2017.10 | — | 47.6 | 12.4 | 23.5 | 16.7 | 68.1 | 84.1 | 26.4 | 39.1 | 35.4 | 65.9 | 52.2 | 45 | 32.4 | — | 42.2 | — | |
| Wolf et al.aggregation=10 random forests2017.10 | — | 74.56 | 17.62 | 62.16 | 47.85 | 82.42 | 98.72 | 26.36 | 69.38 | 48.57 | 83.65 | 25.56 | 54.92 | 31.05 | 39.51 | 55.6 | 64.9 |