List your company

Semantic Segmentation on SYNTHIA to Cityscapes

93.3Road IoUCorDA
80.09283.52186.9590.379Jan 16, 2019Mar 25, 2020Jun 2, 2021Aug 10, 2022Oct 18, 2023Dec 25, 2024Mar 4, 2026

Evaluation results

MethodLinks
CorDA2022.0493.361.685.319.65.137.836.642.884.990.469.741.885.638.432.653.955————————
CorDABackbone=ResNet-101, Framework=DeepLab-v22024.0393.361.685.319.65.137.836.642.884.990.469.741.885.638.432.653.955————————
CorDA (stereo)Depth=Used, Depth Estimation=Stereoscopic2021.0493.361.685.319.651037.836.642.884.990.469.741.885.638.432.653.95562.8———————
UDACTimage translation=true, adversarial training=true, self-supervised learning=true2021.0993.35481.314.37028.821.322.882.683.357.722.883.430.720.247.246.553.9———————
BiMaLNetwork=DL-V22023.0492.851.581.5——30.417.610082.484.655.922.385.738.824.610.246.2—————15.944.530.9
LTIRBackbone=RN-101, Year=2020, Category=Image-to-Image / Style Transfer Methods2021.0592.653.279.2——1.67.578.684.452.62082.134.814.639.4————49.3—————
TIRimage translation=true, adversarial training=true, self-supervised learning=true2021.0992.653.279.2———1.67.578.684.452.62082.134.814.639.4—49.3———————
PixMatch (Fourier + CutMix)Backbone=RN-1012021.0592.554.679.84.780.0824.122.817.879.476.560.824.785.733.526.454.4——46.154.5—————
SEDA (Ours)adversarial training=true, self-supervised learning=true2021.099253.98210.12032.813.32683.684.46321.486.746.824.74948.155.9———————
BAPA2022.0491.753.883.922.40.834.930.542.886.688.26634.186.651.329.450.553.3————————
ATPSource-Free=true2026.0390.654.486.728.50.550.352.450.587.493.470.235.889.653.550.651.159.1————————
TransDANetwork=Trans.2023.0490.454.886.4——53.861.117090.39371.225.392.349.844.431.159.3—————37.16627.3
TransDA-BSource-Free=false2026.0390.454.886.431.11.753.861.137.190.39371.225.392.36644.449.859.3————————
CorDA (mono)Depth=Used, Depth Estimation=Monocular (Monodepth2)2021.0490.247.585.624.530038.241.636.585.991.770.342.48642.934.750.454.562———————
SSASource-Free=true2026.039051.98735.4156.764.653.688.592.378.344.489.863.462.865.164.1————————
FREDOMNetwork=Trans.2023.0489.450.889.3——57.365.193089.993.779.451.690.568.162.348.867—————60.16622
SACNetwork=DL-V22023.0489.347.385.6——43.145.613087.189.163.725.38752.830.326.652.6—————3235.627.9
SACBackbone=ResNet-101, Framework=DeepLab-v22024.0389.347.285.526.51.34345.53287.189.363.625.486.935.630.45352.6————————
DADADepth=Used2021.0489.244.881.46.83026.28.611.181.88454.719.379.740.71438.842.649.8———————
DACSBackbone=ResNet-101, Framework=DeepLab-v2, Guidance Training=true2024.0388.850.48514.12.636.944.444.288.288.469.9458648.939.261.655.6————————
FSTsetting=UDA, base_method=DAFormer2022.0988.346.18841.77.350.153.652.587.491.573.948.185.358.655.963.461.9————————
ProDA2022.0487.845.784.637.10.64454.63788.184.474.224.388.251.140.545.655.5————————
ProDAsetting=UDA2022.0987.845.784.637.10.64454.63788.184.474.224.388.251.140.545.655.5————————
ProDANetwork=DL-V22023.0487.845.784.6——4454.66088.184.474.224.388.245.640.537.155.5—————3751.126.4
ProDABackbone=ResNet-101, Framework=DeepLab-v22024.0387.845.784.637.10.64454.63788.184.474.224.388.251.140.545.655.5————————
MRNet + Oursmethodology=variance regularization2020.0387.641.983.114.71.736.231.319.981.680.66321.886.240.723.653.147.954.9———————
R-MRNetDepth=None2021.0487.641.983.114.717036.231.319.981.680.66321.886.240.723.653.147.954.9———————
CPSLsetting=UDA2022.0987.243.985.533.60.347.757.437.287.888.5793290.649.450.859.857.9————————
DASTadversarial training=true, self-supervised learning=true2021.0987.144.582.310.78029.913.913.181.68660.325.183.140.124.440.545.252.5———————
AdvEntBackbone=RN-101, Year=2019, Category=Adversarial Methods2021.058744.179.79.60.624.34.87.280.183.656.423.772.732.612.833.7——40.847.6—————
APODAArch.=AT2020.0886.441.379.3———22.617.380.381.656.92184.149.124.645.753.1————————
APODA2020.0386.441.379.3———22.617.380.381.656.92184.149.124.645.7—53.1———————
CTRLDepth=Used2021.0486.442.580.42010027.710.513.380.682.66123.781.842.92144.74551.5———————
DAF+IDABackbone=ResNet-101, Framework=DeepLab-v22024.0386.341.681.418.31.325.11110.582.985.662.427.183.955.933.341.246.7————————
CrCDA RBackbone=RN-101, Year=2020, Category=Adversarial Methods2021.0586.244.979.58.30.727.89.411.878.686.557.226.176.839.921.532.1——42.950—————
BLFArch.=A&S2020.088646.780.3———14.111.679.281.354.127.973.742.225.745.351.4————————
BDL2021.038646.780.3———14.111.679.281.354.127.973.742.225.745.3—51.4———————
BDL (M2-F2)Backbone=RN-101, Year=2019, Category=Image-to-Image / Style Transfer Methods2021.058646.780.3——14.111.679.281.354.127.973.742.225.745.3————51.4—————
FREDOMNetwork=DL-V22023.048646.387——48.753.453087.189.171.238.187.159.951.333.359.1—————46.854.624
BDLimage translation=true, adversarial training=true, self-supervised learning=true2021.098646.780.3———14.111.679.281.354.127.973.742.225.745.3—51.4———————
HRDABackbone=ResNet-101, Framework=DeepLab-v2, Guidance Training=false2024.0385.847.387.327.31.450.557.86187.489.176.248.587.349.35568.261.2————————
AdvEntArch.=AT2020.0885.642.279.78.70.425.95.48.180.484.157.923.873.336.414.23341.248———————
AdvEnt2020.0385.642.279.78.70.425.95.48.180.484.157.923.873.336.414.23341.248———————
AdvEnt+MinEntBackbone=RN-101, Year=2019, Category=Adversarial Methods2021.0585.642.279.78.70.425.95.48.180.484.157.923.873.336.414.233——41.248—————
ADVENTDepth=None2021.0485.642.279.78.74025.95.48.180.484.157.923.873.336.414.23341.248———————
ADVENTadversarial training=true2021.0985.642.279.78.74025.95.48.180.484.157.923.873.336.414.23341.248———————
HRDA2022.0485.247.788.849.54.857.265.760.985.392.979.452.88964.763.964.965.8————————
HRDASource-Free=false2026.0385.247.788.849.54.857.265.760.985.392.979.452.88964.763.964.965.8————————
Yang et al.Depth=None2021.0485.144.581———16.415.280.184.859.431.973.24132.644.7—53.1———————
LDRimage translation=true, adversarial training=true, self-supervised learning=true2021.0985.144.581———16.415.280.184.859.431.973.24132.644.7—53.1———————
CAGevaluation_classes=132021.0384.841.785.5———13.72386.578.166.328.181.821.822.949—52.6———————
PixMatch (CutMix)Backbone=RN-1012021.0584.842.1816.980.2527.915.616.682.380.753.921.883.139.32143.1——43.851.2—————
CAGevaluation_classes=162021.0384.740.881.77.8035.113.322.784.577.664.227.880.919.722.748.344.5————————
CAGBackbone=RN-101, Year=2019, Category=Adversarial Methods2021.0584.740.881.77.8035.113.322.784.577.664.227.880.919.722.748.3——44.552.6—————
MICBackbone=ResNet-101, Framework=DeepLab-v2, Guidance Training=false2024.0384.745.788.329.92.853.36159.586.988.878.253.389.458.85668.362.8————————
MICBackbone=ResNet-101, Framework=DeepLab-v2, Guidance Training=true2024.0384.745.38837.32.853.362.561.887.288.578.353.790.460.956.171.463.8————————
SSF-DANArch.=AT2020.0884.641.780.8———11.514.780.885.357.521.6823619.334.550————————
FGGAN2021.0384.540.183.14.8034.320.127.284.88453.522.685.443.726.827.845.252.5———————
FADABackbone=RN-101, Year=2020, Category=Adversarial Methods2021.0584.540.183.14.8034.320.127.284.88453.522.685.443.726.827.8——45.252.5—————
DAFormer2022.0484.540.788.441.56.5505554.68689.873.248.287.253.253.961.760.9————————
DAFormersetting=UDA2022.0984.540.788.441.56.5505554.68689.873.248.287.253.253.961.760.9————————
DAFormerNetwork=Trans.2023.0484.540.788.4——50556508689.873.248.287.261.753.941.560.9—————54.653.222.8
HRDABackbone=ResNet-101, Framework=DeepLab-v2, Guidance Training=true2024.0384.545.58728.72.750.86162.687.788.578.853.589.158.457.268.862.8————————
FADAadversarial training=true, self-supervised learning=true2021.0984.540.183.14.8034.320.127.284.88453.522.685.443.726.827.845.252.5———————
DAFormerSource-Free=false2026.0384.540.788.441.56.5505554.68689.873.248.287.253.253.961.760.9————————
AdaptSegNetArch.=AT2020.0884.342.777.5———4.7777.982.554.32172.332.218.932.346.7————————
AdaptSegNet2020.0384.342.777.5———4.7777.982.554.32172.332.218.932.3—46.7———————
IDA2021.0384.337.779.55.30.424.99.28.48084.157.2237838.120.336.541.748.9———————
IntraDABackbone=RN-101, Year=2020, Category=Other Methods2021.0584.337.779.55.30.424.99.28.48084.157.2237838.120.336.5——41.748.9—————
IntraDANetwork=DL-V22023.0484.337.779.5——24.99.2408084.157.2237836.520.35.341.7—————8.438.131
ProCSTNetwork=Trans.2023.0484.341.187.7——50.755.561086.187.974.747.287.662.553.342.661.4—————54.261.422.6
OutputAdaptDepth=None2021.0484.342.777.5———4.7777.982.554.32172.332.218.932.3—46.7———————
IntraDAadversarial training=true, self-supervised learning=true2021.0984.337.779.55.34024.99.28.48084.157.2237838.120.336.541.748.9———————
AdaptSegNet-LSBackbone=RN-101, Year=2018, Category=Adversarial Methods2021.058440.579.310.40.222.76.5878.382.756.322.47433.218.934.9——40.847.6—————
AdaptMRArch.=A&S2020.0883.138.281.79.3135.130.319.98280.162.821.184.437.824.553.346.553.8———————
MRNet + Pseudo2020.0383.138.281.79.3135.130.319.98280.162.821.184.437.824.553.346.553.8———————
DTST2021.03834480.3———17.115.880.581.859.933.170.237.328.545.8—52.1———————
SIMDepth=None2021.04834480.3———17.115.880.581.859.933.170.237.328.545.8—48.3———————
MS + IW + MultiBackbone=RN-101, Year=2019, Category=Self-Training Methods2021.0582.940.780.310.20.825.812.818.282.582.253.1187931.410.435.6——41.448.2—————
PixMatch (Fourier)Backbone=RN-1012021.0582.936.281.79.740.1129.716.719.284.384.262.316.984.639.43.0452.5——4451.1—————
PLCABackbone=RN-101, Year=2020, Category=Other Methods2021.0582.6298111.20.233.624.918.382.882.362.126.585.648.926.852.2——46.854—————
SIBANArch.=AT2020.0882.52479.4———16.512.779.282.858.31879.325.317.625.946.3————————
SIBAN2020.0382.52479.4———16.512.779.282.858.31879.325.317.625.9—46.3———————
patch-level alignmentBackbone=ResNet-1012019.0182.43878.68.70.6263.911.175.584.653.521.671.432.619.331.74046.5———————
PatchAlignArch.=A&S2020.0882.43878.68.70.6263.911.175.584.653.521.671.432.619.331.74046.5———————
PatchAlign2020.0382.43878.68.70.6263.911.175.584.653.521.671.432.619.331.74046.5———————
Patch-DiscBackbone=RN-101, Year=2019, Category=Adversarial Methods2021.0582.43878.68.70.6263.911.175.584.653.521.671.432.619.331.7——4046.5—————
SWDBackbone=RN-101, Year=2019, Category=Other Methods2021.0582.433.282.5——22.619.783.778.84417.975.430.214.439.9————48.1—————
AdaptPatchadversarial training=true2021.0982.43878.68.760263.911.175.584.653.521.671.432.619.331.74046.5———————
IDMSource-Free=true2026.0382.237.983.520.31.547.341.725.684.486.861.62587.643.730.236.449.7————————
PixMatch (Style)Backbone=RN-1012021.0582.13876.23.970.1226.414.21175.570.754.320.675.836.919.439.3——40.347.3—————
MRNet2020.038236.580.44.20.433.71813.481.180.861.321.784.432.414.845.743.250.2———————
IAST(ours)Arch.=A&S2020.0881.941.583.317.74.632.330.928.883.48565.530.886.538.233.152.749.857———————
IASTBackbone=ResNet-101, Framework=DeepLab-v22024.0381.941.583.317.74.632.330.928.883.48565.530.886.538.233.152.749.8————————
IASTDepth=None2021.0481.941.583.317.746032.330.928.883.48565.530.886.538.233.152.749.857———————
AdaSegNetadversarial training=true2021.0981.739.178.411.13025.86.8979.180.854.82166.834.713.829.939.645.8———————
CLAN2020.0381.33780.1———16.113.778.281.553.421.27332.922.630.7—47.8———————
CLANadversarial training=true2021.0981.33780.1———16.113.778.281.553.421.27332.922.630.7—47.8———————
DACS2022.0480.625.181.921.52.937.222.72483.790.867.638.382.938.928.547.648.3————————
DACSBackbone=ResNet-101, Framework=DeepLab-v2, Guidance Training=false2024.0380.625.181.921.52.937.222.72483.790.867.638.382.938.928.547.648.3————————