Semantic Segmentation on PASCAL-Context 60 classes (test)
55.5mIoUCTNet
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| CTNetBackbone=ResNet-1012021.04 | 55.5 | — | — | |
| OCRBackbone=ResNet-1012021.04 | 54.8 | — | — | |
| APCNetBackbone=ResNet-1012021.04 | 54.7 | — | — | |
| SPNetBackbone=ResNet-1012021.04 | 54.5 | — | — | |
| ACNetBackbone=ResNet-1012021.04 | 54.1 | — | — | |
| CFNetBackbone=ResNet-1012021.04 | 54 | — | — | |
| CPNBackbone=ResNet-1012021.04 | 53.9 | — | — | |
| SFNetBackbone=ResNet-101, Inference Scale=multi-scale, #GFLOPs=93.62020.02 | 53.8 | — | — | |
| BAFPNetBackbone=ResNet-101, Inference Scale=multi-scale2020.02 | 53.6 | — | — | |
| SVCNetBackbone=ResNet-1012021.04 | 53.2 | — | — | |
| EMANetBackbone=ResNet-101, Inference Scale=multi-scale, #GFLOPs=209.32020.02 | 53.1 | — | — | |
| FastFCNBackbone=ResNet-1012021.04 | 53.1 | — | — | |
| EMANetBackbone=ResNet-1012021.04 | 53.1 | — | — | |
| CTNetBackbone=ResNet-502021.04 | 52.9 | — | — | |
| ANNetBackbone=ResNet-101, Inference Scale=multi-scale, #GFLOPs=243.82020.02 | 52.8 | — | — | |
| DANetBackbone=ResNet-101, Inference Scale=multi-scale, #GFLOPs=257.12020.02 | 52.6 | — | — | |
| DANetBackbone=ResNet-1012021.04 | 52.6 | — | — | |
| EncNetBaseNet=Res1012018.03 | 51.7 | — | — | |
| EncNetBackbone=ResNet-101, Inference Scale=multi-scale2020.02 | 51.7 | — | — | |
| EncNetBackbone=ResNet-1012021.04 | 51.7 | — | — | |
| Ding et al.Backbone=ResNet-101, Inference Scale=multi-scale2020.02 | 51.6 | — | — | |
| SFNet (w/o FAM)Backbone=ResNet-101, Inference Scale=multi-scale, #GFLOPs=92.72020.02 | 51.1 | — | — | |
| SFNetBackbone=ResNet-50, Inference Scale=multi-scale, #GFLOPs=75.42020.02 | 50.7 | — | — | |
| MSCIBackbone=ResNet-1522021.04 | 50.3 | — | — | |
| DANetBackbone=ResNet-50, Inference Scale=multi-scale, #GFLOPs=186.42020.02 | 50.1 | — | — | |
| EncNetBackbone=ResNet-50, Inference Scale=multi-scale2020.02 | 49.2 | — | — | |
| SFNet (w/o FAM)Backbone=ResNet-50, Inference Scale=multi-scale, #GFLOPs=74.52020.02 | 49 | — | — | |
| PSPNetBackbone=ResNet-1012021.04 | 47.8 | — | — | |
| RefineNet-Res152Backbone=ResNet-152, Extra train data=none2016.11 | 47.3 | — | — | |
| RefineNetBaseNet=Res1522018.03 | 47.3 | — | — | |
| RefineNetBackbone=ResNet-1522021.04 | 47.3 | — | — | |
| RefineNet-Res101Backbone=ResNet-101, Extra train data=none2016.11 | 47.1 | — | — | |
| DeepLab-v2Backbone=ResNet-101, Extra train data=COCO (~100K)2016.11 | 45.7 | — | — | |
| DeepLab-v2BaseNet=Res101-COCO2018.03 | 45.7 | — | — | |
| VeryDeep2018.03 | 44.5 | — | — | |
| VeryDeep2021.04 | 44.5 | — | — | |
| Contextual Deep CRFs2015.04 | 43.3 | 71.5 | 53.9 | |
| ContextExtra train data=none2016.11 | 43.3 | — | — | |
| Piecewise2018.03 | 43.3 | — | — | |
| HO-CRFExtra train data=none2016.11 | 41.3 | — | — | |
| HO_CRF2018.03 | 41.3 | — | — | |
| BoxSup2015.04 | 40.5 | — | — | |
| BoxSupExtra train data=none2016.11 | 40.5 | — | — | |
| BoxSup2018.03 | 40.5 | — | — | |
| ParseNet2018.03 | 40.4 | — | — | |
| CRF-RNN2018.03 | 39.3 | — | — | |
| FCN-8s2018.03 | 37.8 | — | — | |
| FCN2021.04 | 37.8 | — | — | |
| FCN-8s2015.04 | 35.1 | 65.9 | 46.5 | |
| FCN-8sExtra train data=none2016.11 | 35.1 | — | — | |
| CFM2015.04 | 34.4 | — | — | |
| CFMExtra train data=none2016.11 | 34.4 | — | — | |
| O2P2015.04 | 18.1 | — | — | |
| O2PExtra train data=none2016.11 | 18.1 | — | — |