Semi Supervised Semantic Segmentation On 28

Metriken

Validation mIoU

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
UniMatch V2 (DINOv2-B)	87.9	UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation
SemiVL (ViT-B/16)	85.6	SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance
UniMatch (ViT-B/16)	80.1	SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance
PrevMatch (ResNet-101)	78.5	Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation
CorrMatch (Deeplabv3+ with ResNet-101)	78.5	CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation
AllSpark	78.41	AllSpark: Reborn Labeled Features from Unlabeled in Transformer for Semi-Supervised Semantic Segmentation
UniMatch (DeepLab v3+ with ResNet-101)	77.20	Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation
LogicDiag (DeepLab v3+ with ResNet-101)	76.7	Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation
PrevMatch (ResNet-50)	75.4	Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation
S4MC	75.21	Semi-Supervised Semantic Segmentation via Marginal Contextual Information
U2PL (DeepLab v3+ with ResNet-101)	69.2	Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
CPS (DeepLab v3+ with ResNet-101)	67.4	Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
CPCL (DeepLab v3+ with ResNet-50)	67.02	Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation

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