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SOTA
Domain Adaptation
Domain Adaptation On Cityscapes To Acdc
Domain Adaptation On Cityscapes To Acdc
Métriques
mIoU
Résultats
Résultats de performance de divers modèles sur ce benchmark
Columns
Nom du modèle
mIoU
Paper Title
Repository
DACS (DeepLabv2)
41.2
DACS: Domain Adaptation via Cross-domain Mixed Sampling
Refign (DAFormer)
65.5
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
DAFormer
55.4
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
VBLC (DeepLabv2)
47.8
VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions
MIC
70.4
MIC: Masked Image Consistency for Context-Enhanced Domain Adaptation
CMFormer
60.1
Learning Content-enhanced Mask Transformer for Domain Generalized Urban-Scene Segmentation
Refign (HRDA)
72.1
Refign: Align and Refine for Adaptation of Semantic Segmentation to Adverse Conditions
SoRA
78.8
SoRA: Singular Value Decomposed Low-Rank Adaptation for Domain Generalizable Representation Learning
DANNet
50.0
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
FDA (DeepLabv2)
45.7
FDA: Fourier Domain Adaptation for Semantic Segmentation
VBLC (DAFormer)
64.2
VBLC: Visibility Boosting and Logit-Constraint Learning for Domain Adaptive Semantic Segmentation under Adverse Conditions
HRDA
68.0
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
Rein
77.6
Stronger, Fewer, & Superior: Harnessing Vision Foundation Models for Domain Generalized Semantic Segmentation
MGCDA
48.7
Map-Guided Curriculum Domain Adaptation and Uncertainty-Aware Evaluation for Semantic Nighttime Image Segmentation
CoDA
72.6
CoDA: Instructive Chain-of-Domain Adaptation with Severity-Aware Visual Prompt Tuning
HALO
71.9
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
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