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Semi-Supervised Semantic Segmentation

Models that are trained with a small number of labeled examples and a large number of unlabeled examples and whose aim is to learn to segment an image (i.e. assign a class to every pixel).

Papers

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Showing 1–25 of 190 papers

TitleStatusHype
SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation—0
DEARLi: Decoupled Enhancement of Recognition and Localization for Semi-supervised Panoptic SegmentationCode0
Leveraging Out-of-Distribution Unlabeled Images: Semi-Supervised Semantic Segmentation with an Open-Vocabulary ModelCode0
HierVL: Semi-Supervised Segmentation leveraging Hierarchical Vision-Language Synergy with Dynamic Text-Spatial Query Alignment—0
FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic SegmentationCode0
RS-MTDF: Multi-Teacher Distillation and Fusion for Remote Sensing Semi-Supervised Semantic SegmentationCode1
Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation—0
Zero-Shot Pseudo Labels Generation Using SAM and CLIP for Semi-Supervised Semantic Segmentation—0
Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation—0
IGL-DT: Iterative Global-Local Feature Learning with Dual-Teacher Semantic Segmentation Framework under Limited Annotation Scheme—0
BoundMatch: Boundary detection applied to semi-supervised segmentation for urban-driving scenes—0
Semi-supervised Semantic Segmentation with Multi-Constraint Consistency LearningCode0
Knowledge Consultation for Semi-Supervised Semantic Segmentation—0
Exploring Token-Level Augmentation in Vision Transformer for Semi-Supervised Semantic SegmentationCode0
Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic SegmentationCode0
Semi-supervised Semantic Segmentation for Remote Sensing Images via Multi-scale Uncertainty Consistency and Cross-Teacher-Student AttentionCode1
Uncertainty and Energy based Loss Guided Semi-Supervised Semantic Segmentation—0
Improving Semi-Supervised Semantic Segmentation with Sliced-Wasserstein Feature Alignment and Uniformity—0
Uncertainty-Participation Context Consistency Learning for Semi-supervised Semantic SegmentationCode1
Biologically-inspired Semi-supervised Semantic Segmentation for Biomedical ImagingCode0
Masked Image Modeling Boosting Semi-Supervised Semantic SegmentationCode0
Revisiting Network Perturbation for Semi-Supervised Semantic SegmentationCode0
UniMatch V2: Pushing the Limit of Semi-Supervised Semantic SegmentationCode3
Learning from Spatio-temporal Correlation for Semi-Supervised LiDAR Semantic SegmentationCode0
Exploiting Minority Pseudo-Labels for Semi-Supervised Semantic Segmentation in Autonomous Driving—0
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