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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 141–150 of 190 papers

TitleStatusHype
Learning High-Resolution Domain-Specific Representations with a GAN Generator—0
Locating Noise is Halfway Denoising for Semi-Supervised Segmentation—0
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation—0
Looking Beyond Single Images for Contrastive Semantic Segmentation Learning—0
Mapping Temporary Slums from Satellite Imagery using a Semi-Supervised Approach—0
Mask-based Data Augmentation for Semi-supervised Semantic Segmentation—0
Multi-Level Label Correction by Distilling Proximate Patterns for Semi-supervised Semantic Segmentation—0
Multi-View Correlation Consistency for Semi-Supervised Semantic Segmentation—0
Navya3DSeg -- Navya 3D Semantic Segmentation Dataset & split generation for autonomous vehicles—0
360^ from a Single Camera: A Few-Shot Approach for LiDAR Segmentation—0
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