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Semantic Segmentation on GTA5

60.7mIoUCMFormer
25.142434.373743.60552.8363Jul 1, 2023Sep 19, 2023Dec 9, 2023Feb 28, 2024May 19, 2024Aug 8, 2024Oct 28, 2024

Evaluation results

MethodLinks
CMFormerBackbone=Swin-L, Trained on Cityscapes=true2023.0760.7
HGFormerBackbone=Swin-L, Trained on Cityscapes=true2023.0759.4
CMFormerBackbone=Swin-B, Trained on Cityscapes=true2023.0758.11
Mask2FormerBackbone=Swin-L, Trained on Cityscapes=true2023.0757.8
Mask2FormerBackbone=Swin-B, Trained on Cityscapes=true2023.0755.05
HGFormerBackbone=Swin-T, Trained on Cityscapes=true2023.0751.3
Mask2FormerBackbone=Swin-T, Trained on Cityscapes=true2023.0750.6
SHADEBackbone=ResNet50, Trained on Cityscapes=true2023.0748.61
SAWBackbone=ResNet50, Trained on Cityscapes=true2023.0747.28
WildNetBackbone=ResNet50, Trained on Cityscapes=true2023.0747.01
DIRLBackbone=ResNet50, Trained on Cityscapes=true2023.0746.52
GTRBackbone=ResNet50, Trained on Cityscapes=true2023.0745.79
IternormBackbone=ResNet50, Trained on Cityscapes=true2023.0745.73
DRPCBackbone=ResNet50, Trained on Cityscapes=true2023.0745.62
IBNBackbone=ResNet50, Trained on Cityscapes=true2023.0745.06
ISWBackbone=ResNet50, Trained on Cityscapes=true2023.0745
IWBackbone=ResNet50, Trained on Cityscapes=true2023.0744.87
ULDASource Domain=Cityscapes, Prompt=driving in a game, Backbone=CLIP-ResNet-50, Base Model=DeepLabv3+2024.0442.91
PØDAAdaptation setting=0-shot, Prompt=driving in a game2024.1041.07
PØDASource domain=Cityscapes (CS), Target prompt (P)=driving in a game, Zero-shot domain adaptation=true2024.1041.07
PIDAAdaptation setting=1-shot, Target image usage=single target image2024.1041.02
PØDASource Domain=Cityscapes, Prompt=driving in a game, Backbone=CLIP-ResNet-50, Base Model=DeepLabv3+2024.0440.77
CMFormerTrained on=SYNTHIA (S)2023.0740.65
AdaINAdaptation setting=1-shot, Target image usage=single target image2024.1040.56
source-onlySource Domain=Cityscapes, Prompt=driving in a game, Backbone=CLIP-ResNet-50, Base Model=DeepLabv3+2024.0439.59
source-only2024.1039.59
source-onlySource domain=Cityscapes (CS), Target prompt (P)=driving in a game, Zero-shot domain adaptation=true2024.1039.59
CLIPstylerSource Domain=Cityscapes, Prompt=driving in a game, Backbone=CLIP-ResNet-50, Base Model=DeepLabv3+2024.0438.73
CLIPstylerSource domain=Cityscapes (CS), Target prompt (P)=driving in a game, Zero-shot domain adaptation=true2024.1038.73
SAWTrained on=SYNTHIA (S)2023.0729.16
DRPCTrained on=SYNTHIA (S)2023.0728.75
GTRTrained on=SYNTHIA (S)2023.0728.02
ISWTrained on=SYNTHIA (S)2023.0727.68
IBNTrained on=SYNTHIA (S)2023.0726.9
IWTrained on=SYNTHIA (S)2023.0726.51