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Semantic Segmentation on DADA-seg (test)

47mIoUMMUDA
7.4817.742838.26Dec 9, 2021Dec 25, 2021Jan 11, 2022Jan 28, 2022Feb 13, 2022Mar 2, 2022Mar 19, 2022

Evaluation results

MethodLinks
MMUDAInput size=768x7682022.0347————————————————————105.530.49
Trans4Trans-MInput size=768x7682022.0339.2————————————————————41.949.55
SETR-PUPBackbone=Transformer-Large, Resolution=768x7682021.1231.8———————————————————-47.5——
SETR-MLABackbone=Transformer-Large, Resolution=768x7682021.1230.4———————————————————-46.8——
EDCNetResolution=1024x5122021.1229.9780.2319.5152.026.4314.6816.1917.0319.565.3921.6979.849.958.8265.639.5139.73—6.097.03———
BDLResolution=1024x5122021.1229.6681.4419.1857.188.6116.2614.658.7816.7766.626.8385.8710.517.1665.4535.1834.78—2.715.57———
CLANResolution=1024x5122021.1228.7679.818.6151.568.3213.615.5117.1521.5163.221.9980.538.376.3263.4733.4333.12—3.696.21———
HRNetInput size=768x7682022.0327.5————————————————————210.565.86
SETR-NaiveBackbone=Transformer-Large, Resolution=768x7682021.1227.1———————————————————-50.8——
SegFormer-B3Backbone=MiT-B3, Resolution=768x7682021.1227———————————————————-54.5——
SIMResolution=1024x5122021.1226.8579.1316.9356.794.6912.3816.57.4714.0465.7818.1787.2711.043.8361.3322.9928.21—0.522.96———
DeepLabV3+Input size=768x7682022.0326.8————————————————————178.118.7
Fast-SCNNBackbone=Fast-SCNN, Resolution=1024x5122021.1226.3———————————————————-42.8——
OCRNetBackbone=HRNetV2p-W48, Resolution=1024x5122021.1224.5———————————————————-56.2——
FDAResolution=1024x5122021.1224.4567.8315.3639.994.2812.9816.086.9318.2657.019.7164.510.39.4959.3916.8439.35—11.284.94———
OCRNetBackbone=HRNetV2p-W18, Resolution=1024x5122021.1223———————————————————-55.6——
SegFormer-B2Backbone=MiT-B2, Resolution=768x7682021.1221.2———————————————————-59.3——
DeepLabV3+Backbone=ResNet-101, Resolution=1024x5122021.1221———————————————————-59.9——
SwiftNetBackbone=ResNet-18, Resolution=1024x5122021.1220.5———————————————————-54.9——
OCRNetBackbone=HRNetV2p-W18s, Resolution=1024x5122021.1220.5———————————————————-56.6——
PSPNetBackbone=ResNet-101, Resolution=1024x5122021.1220.1———————————————————-59.7——
ResNeStBackbone=ResNeSt-101, Resolution=1024x5122021.1220———————————————————-59.6——
DNLBackbone=ResNet-101, Resolution=1024x5122021.1219.7———————————————————-60.7——
Semantic FPNBackbone=ResNet-101, Resolution=1024x5122021.1219.6———————————————————-56.2——
DeepLabV3+Backbone=ResNet-18, Resolution=1024x5122021.1219.1———————————————————-57.7——
MobileNetV3Backbone=MobileNetV3small, Resolution=1024x5122021.1218.2———————————————————-45.9——
Semantic FPNBackbone=ResNet-50, Resolution=1024x5122021.1218.2———————————————————-56.3——
DeepLabV3+Backbone=ResNet-50, Resolution=1024x5122021.1218———————————————————-62.1——
DANetBackbone=ResNet-101, Resolution=1024x5122021.1217.8———————————————————-62.6——
MobileNetV3Backbone=MobileNetV3, Resolution=1024x5122021.1217.6———————————————————-51.9——
DANetBackbone=ResNet-50, Resolution=1024x5122021.1217.6———————————————————-61.7——
PSPNetBackbone=MobileNet V2, Resolution=1024x5122021.1217.1———————————————————-52.5——
SegFormer-B1Backbone=MiT-B1, Resolution=768x7682021.1216.6———————————————————-61.4——
DeepLabV3+Backbone=MobileNet V2, Resolution=1024x5122021.1216.5———————————————————-58.7——
PSPNetBackbone=ResNet-50, Resolution=1024x5122021.1216.1———————————————————-62.5——
DNLBackbone=ResNet-50, Resolution=1024x5122021.1215.7———————————————————-63.6——
ERFNetBackbone=ERFNet, Resolution=1024x5122021.129———————————————————-63.1——