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プラットフォーム
ホーム
SOTA
半教師付きセマンティックセグメンテーション
Semi Supervised Semantic Segmentation On 22
Semi Supervised Semantic Segmentation On 22
評価指標
Validation mIoU
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
Columns
モデル名
Validation mIoU
Paper Title
UniMatch V2 (DINOv2-B)
83.6
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic Segmentation
SemiVL (ViT-B/16)
77.9
SemiVL: Semi-Supervised Semantic Segmentation with Vision-Language Guidance
PrevMatch (ResNet-101)
77.7%
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation
CorrMatch (Deeplabv3+ with ResNet-101)
77.3
CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic Segmentation
S4MC
77.00
Semi-Supervised Semantic Segmentation via Marginal Contextual Information
Dual Teacher (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K)
76.81
Switching Temporary Teachers for Semi-Supervised Semantic Segmentation
UniMatch (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K)
76.59
Revisiting Weak-to-Strong Consistency in Semi-Supervised Semantic Segmentation
n-CPS (ResNet-50)
76.08
n-CPS: Generalising Cross Pseudo Supervision to n Networks for Semi-Supervised Semantic Segmentation
AEL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K)
75.83%
Semi-Supervised Semantic Segmentation via Adaptive Equalization Learning
PrevMatch (ResNet-50)
75.8%
Revisiting and Maximizing Temporal Knowledge in Semi-supervised Semantic Segmentation
CW-BASS (DeepLab v3+ with ResNet-50)
75.00
CW-BASS: Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation
U2PL (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K, AEL)
74.90%
Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels
PCR (DeepLab v3+ with ResNet-101 pretraind on ImageNet-1K)
73.41%
Semi-supervised Semantic Segmentation with Prototype-based Consistency Regularization
Dense FixMatch (DeepLabv3+ ResNet-101, over-sampling, single pass eval)
71.1%
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks
Dense FixMatch (DeepLabv3+ ResNet-50, uniform sampling, single pass eval)
70.65%
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasks
CPCL (DeepLab v3+ with ResNet-50)
69.92%
Conservative-Progressive Collaborative Learning for Semi-supervised Semantic Segmentation
CPS (DeepLab v3+ with ResNet-101)
69.8
Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
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