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SOTA
Semi-Supervised Semantic Segmentation
Semi Supervised Semantic Segmentation On 30
Semi Supervised Semantic Segmentation On 30
Metrics
Validation mIoU
Results
Performance results of various models on this benchmark
Columns
Model Name
Validation mIoU
Paper Title
UniMatch V2 (DINOv2-B)
90.0
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation
SemiVL (ViT-B/16)
86.7
SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance
UniMatch (ViT-B/16)
83.3
SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance
AllSpark
80.75
AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation
CorrMatch (Deeplabv3+ with ResNet-101)
80.6
CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation
PrevMatch (ResNet-101)
80.4
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation
S4MC
80.12
Semi-Supervised Semantic Segmentation via Marginal Contextual Information
UniMatch (DeepLab v3+ with ResNet-101)
79.90
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation
LogicDiag (DeepLab v3+ with ResNet-101)
79.4
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation
PrevMatch (ResNet-50)
78.6
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation
S4MC (R50)
77.83
Semi-Supervised Semantic Segmentation via Marginal Contextual Information
U2PL (DeepLab v3+ with ResNet-101)
76.2
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
CPS (DeepLab v3+ with ResNet-101)
75.9
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
CPCL (DeepLab v3+ with ResNet-50)
74.25
Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation
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Semi Supervised Semantic Segmentation On 30 | SOTA | HyperAI