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الرئيسية
SOTA
Domain Adaptation
Domain Adaptation On Synthia To Cityscapes
Domain Adaptation On Synthia To Cityscapes
المقاييس
mIoU
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
Columns
اسم النموذج
mIoU
Paper Title
Repository
PyCDA (VGG-16)
35.9
Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach
MIC + Guidance Training
63.8
Improve Cross-domain Mixed Sampling with Guidance Training for Adaptive Segmentation
CD-AM (VGG-16)
40.8
Context-Aware Domain Adaptation in Semantic Segmentation
-
MIC
67.3
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
STPL
51.8
Spatio-Temporal Pixel-Level Contrastive Learning-based Source-Free Domain Adaptation for Video Semantic Segmentation
SAC (ResNet-101)
52.6
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation
ProDA+CRA
56.9
Cross-Region Domain Adaptation for Class-level Alignment
-
SePiCo (DeepLabv2-ResNet-101)
58.1
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
-
LDR (VGG-16)
41.1
Label-Driven Reconstruction for Domain Adaptation in Semantic Segmentation
-
PIT (VGG-16)
38.1
Cross-Domain Semantic Segmentation via Domain-Invariant Interactive Relation Transfer
-
HALO
78.1
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
PyCDA (ResNet-101)
46.7
Constructing Self-motivated Pyramid Curriculums for Cross-Domain Semantic Segmentation: A Non-Adversarial Approach
FDA (VGG-16)
40.5
FDA: Fourier Domain Adaptation for Semantic Segmentation
FREDOM - Transformer
67
FREDOM: Fairness Domain Adaptation Approach to Semantic Scene Understanding
BiMaL
46.2
BiMaL: Bijective Maximum Likelihood Approach to Domain Adaptation in Semantic Scene Segmentation
FADA (ResNet-101)
45.2
Classes Matter: A Fine-grained Adversarial Approach to Cross-domain Semantic Segmentation
IAST (ResNet-101)
49.8
Instance Adaptive Self-Training for Unsupervised Domain Adaptation
SePiCo
64.3
SePiCo: Semantic-Guided Pixel Contrast for Domain Adaptive Semantic Segmentation
-
ILM-ASSL
76.6
Iterative Loop Method Combining Active and Semi-Supervised Learning for Domain Adaptive Semantic Segmentation
DCF
69.3
Transferring to Real-World Layouts: A Depth-aware Framework for Scene Adaptation
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