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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 76–100 of 190 papers

TitleStatusHype
Enhanced Soft Label for Semi-Supervised Semantic Segmentation—0
Large-Scale Land Cover Mapping with Fine-Grained Classes via Class-Aware Semi-Supervised Semantic Segmentation—0
Locating Noise is Halfway Denoising for Semi-Supervised Segmentation—0
Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups—0
XNet: Wavelet-Based Low and High Frequency Fusion Networks for Fully- and Semi-Supervised Semantic Segmentation of Biomedical ImagesCode2
CauSSL: Causality-inspired Semi-supervised Learning for Medical Image SegmentationCode1
Pseudo-Label Guided Contrastive Learning for Semi-Supervised Medical Image SegmentationCode1
Hunting Sparsity: Density-Guided Contrastive Learning for Semi-Supervised Semantic SegmentationCode1
Semi-Supervised Semantic Segmentation Methods for UW-OCTA Diabetic Retinopathy Grade Assessment—0
Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic SegmentationCode1
Conservative-Progressive Collaborative Learning for Semi-supervised Semantic SegmentationCode1
Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation—0
Instance-specific and Model-adaptive Supervision for Semi-supervised Semantic SegmentationCode1
L-MAE: Masked Autoencoders are Semantic Segmentation Datasets Augmenter—0
Boosting Semi-Supervised Semantic Segmentation with Probabilistic RepresentationsCode1
Pseudo-Label Noise Suppression Techniques for Semi-Supervised Semantic SegmentationCode0
Dense FixMatch: a simple semi-supervised learning method for pixel-wise prediction tasksCode0
Fuzzy Positive Learning for Semi-supervised Semantic Segmentation—0
Semi-supervised Semantic Segmentation with Prototype-based Consistency RegularizationCode1
COARSE3D: Class-Prototypes for Contrastive Learning in Weakly-Supervised 3D Point Cloud SegmentationCode1
Learning from Future: A Novel Self-Training Framework for Semantic SegmentationCode1
Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students—0
Semi-Supervised Semantic Segmentation with Cross Teacher TrainingCode0
Semi-supervised Semantic Segmentation with Mutual Knowledge DistillationCode1
Multi-Granularity Distillation Scheme Towards Lightweight Semi-Supervised Semantic SegmentationCode1
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