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SOTA
Synthetic To Real Translation
Synthetic To Real Translation On Synthia To 1
Synthetic To Real Translation On Synthia To 1
評価指標
MIoU (13 classes)
MIoU (16 classes)
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
MIoU (13 classes)
MIoU (16 classes)
Paper Title
Repository
MetaCorrection(ResNet-101)
52.5
45.1
MetaCorrection: Domain-aware Meta Loss Correction for Unsupervised Domain Adaptation in Semantic Segmentation
TransDA-B
66.3
59.3
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
DACS(ResNet-101)
54.81
48.34
DACS: Domain Adaptation via Cross-domain Mixed Sampling
DCF
75.9
69.3
Transferring to Real-World Layouts: A Depth-aware Framework for Scene Adaptation
HRDA
72.4
65.8
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
EHTDI
64.6
57.8
Exploring High-quality Target Domain Information for Unsupervised Domain Adaptive Semantic Segmentation
AdaptSegNet(Multi-level)
46.7
-
Learning to Adapt Structured Output Space for Semantic Segmentation
SePiCo
71.4
64.3
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
-
CLUDA+HRDA
-
67.2
CLUDA : Contrastive Learning in Unsupervised Domain Adaptation for Semantic Segmentation
FADA(ResNet-101)
52.5
45.2
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
MIC
74.0
67.3
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
CAMix (w DAFormer)
69.2
-
Context-Aware Mixup for Domain Adaptive Semantic Segmentation
CAG-UDA
52.6
44.5
Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
ProDA(ResNet-101)
62.0
55.5
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation
CAMix (ResNet 101)
59.7
-
Context-Aware Mixup for Domain Adaptive Semantic Segmentation
CLAN
47.8
-
Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation
Uncertainty + Adaboost (ResNet-101)
57.5
50.4
Adaptive Boosting for Domain Adaptation: Towards Robust Predictions in Scene Segmentation
G2L
64.4
56.8
G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation
-
IAST(ResNet-101)
57.0
49.8
Instance Adaptive Self-Training for Unsupervised Domain Adaptation
ITEN
-
46.45
Exploiting Image Translations via Ensemble Self-Supervised Learning for Unsupervised Domain Adaptation
-
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