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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 161–170 of 190 papers

TitleStatusHype
Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network—0
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised LearningCode1
Part-aware Prototype Network for Few-shot Semantic SegmentationCode1
Learning High-Resolution Domain-Specific Representations with a GAN Generator—0
DMT: Dynamic Mutual Training for Semi-Supervised LearningCode1
Semi-Supervised Semantic Segmentation with Cross-Consistency TrainingCode1
Structured Consistency Loss for semi-supervised semantic segmentation—0
Discovering Latent Classes for Semi-Supervised Semantic Segmentation—0
Saliency Guided Self-attention Network for Weakly and Semi-supervised Semantic SegmentationCode0
Semi-supervised Semantic Segmentation using Auxiliary Network—0
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