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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 111–120 of 190 papers

TitleStatusHype
Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation—0
360^ from a Single Camera: A Few-Shot Approach for LiDAR Segmentation—0
Semi-Supervised Semantic Segmentation via Marginal Contextual InformationCode0
Logic-induced Diagnostic Reasoning for Semi-supervised Semantic Segmentation—0
Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learning—0
Space Engage: Collaborative Space Supervision for Contrastive-based Semi-Supervised Semantic Segmentation—0
Boundary-Refined Prototype Generation: A General End-to-End Paradigm for Semi-Supervised Semantic SegmentationCode0
TrueDeep: A systematic approach of crack detection with less data—0
Semi-Supervised Semantic Segmentation With Region RelevanceCode0
CAFS: Class Adaptive Framework for Semi-Supervised Semantic SegmentationCode0
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