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SOTA
域适应
Domain Adaptation On Gta5 To Cityscapes
Domain Adaptation On Gta5 To Cityscapes
评估指标
mIoU
评测结果
各个模型在此基准测试上的表现结果
Columns
模型名称
mIoU
Paper Title
Repository
HALO
77.8
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
DCF
77.7
Transferring to Real-World Layouts: A Depth-aware Framework for Scene Adaptation
ILM-ASSL
76.1
Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentation
MIC
75.9
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
HRDA+PiPa
75.6
PiPa: Pixel- and Patch-wise Self-supervised Learning for Domain Adaptative Semantic Segmentation
HRDA
73.8
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
FREDOM - Transformer
73.6
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding
SePiCo
70.3
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
DAFormer + ProCST
69.4
ProCST: Boosting Semantic Segmentation Using Progressive Cyclic Style-Transfer
DAFormer
68.3
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
MIC + Guidance Training
67.0
Improve Cross-domain Mixed Sampling with Guidance Training for Adaptive Segmentation
TransDA-B
63.9
Smoothing Matters: Momentum Transformer for Domain Adaptive Semantic Segmentation
DDB
62.7
Deliberated Domain Bridging for Domain Adaptive Semantic Segmentation
EHTDI*
62.0
Exploring High-quality Target Domain Information for Unsupervised Domain Adaptive Semantic Segmentation
FREDOM - DeepLabV2
61.3
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding
BiSMAP
61.2
Bidirectional Self-Training with Multiple Anisotropic Prototypes for Domain Adaptive Semantic Segmentation
G2L
59.7
G2L: A Global to Local Alignment Method for Unsupervised Domain Adaptive Semantic Segmentation
-
FAFS
58.8
A Novel Unsupervised Domain Adaption Method for Depth-Guided Semantic Segmentation Using Coarse-to-Fine Alignment
-
ProDA+CRA
58.6
Cross-Region Domain Adaptation for Class-level Alignment
-
ProDA
57.5
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation
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