Semantic Segmentation on NYUD v2 13-class (test)
76Mean AccuracyShapeConv
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| ShapeConvmulti-scale testing=true2021.08 | 76 | 82.9 | 65.6 | 71.6 | |
| ShapeConv2021.08 | 75.7 | 82.6 | 65.1 | 71.2 | |
| PVNetmulti-scale testing=true2021.08 | 74.4 | 82.5 | 59.3 | — | |
| MVCNetmulti-scale testing=true2021.08 | 70.6 | 79.1 | 59.1 | — | |
| MVCNet2021.08 | 69.5 | 77.8 | 57.3 | — | |
| STD2Pvariant=full model2016.04 | 68.4 | 75.8 | — | — | |
| STD2Pvariant=superpixel+2016.04 | 67 | 74.8 | — | — | |
| Eigen et al.2016.04 | 66.9 | 75.4 | — | — | |
| Eigen2021.08 | 66.9 | 75.4 | — | — | |
| McCormac et al.2016.04 | 63.6 | 69.9 | — | — | |
| Wang et al.reference=[39]2016.04 | 52.7 | 74.7 | — | — | |
| Hermans et al.2016.04 | 48 | 54.2 | — | — | |
| Wang et al.reference=[38]2016.04 | 42.2 | — | — | — | |
| Couprie et al.2016.04 | 36.2 | 52.4 | — | — |