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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
Zero-Shot Pseudo Labels Generation Using SAM and CLIP for Semi-Supervised Semantic Segmentation—0
Adaptive Spatial Augmentation for Semi-supervised Semantic Segmentation—0
Anti-Adversarially Manipulated Attributions for Weakly Supervised Semantic Segmentation and Object Localization—0
A Survey on Semi-Supervised Semantic Segmentation—0
BoundMatch: Boundary detection applied to semi-supervised segmentation for urban-driving scenes—0
C3-SemiSeg: Contrastive Semi-Supervised Segmentation via Cross-Set Learning and Dynamic Class-Balancing—0
CFCG: Semi-Supervised Semantic Segmentation via Cross-Fusion and Contour Guidance Supervision—0
Colour augmentation for improved semi-supervised semantic segmentation—0
Consistency Regularisation in Varying Contexts and Feature Perturbations for Semi-Supervised Semantic Segmentation of Histology Images—0
Discovering Latent Classes for Semi-Supervised Semantic Segmentation—0
DiverseNet: Decision Diversified Semi-supervised Semantic Segmentation Networks for Remote Sensing Imagery—0
Enhanced Soft Label for Semi-Supervised Semantic Segmentation—0
Feature-enhanced Adversarial Semi-supervised Semantic Segmentation Network for Pulmonary Embolism Annotation—0
Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation—0
Few Labeled Atlases are Necessary for Deep-Learning-Based Segmentation—0
FixMatchSeg: Fixing FixMatch for Semi-Supervised Semantic Segmentation—0
GuidedMix-Net: Semi-supervised Semantic Segmentation by Using Labeled Images as Reference—0
HierVL: Semi-Supervised Segmentation leveraging Hierarchical Vision-Language Synergy with Dynamic Text-Spatial Query Alignment—0
Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image—0
IGL-DT: Iterative Global-Local Feature Learning with Dual-Teacher Semantic Segmentation Framework under Limited Annotation Scheme—0
Improved Training for Self-Training by Confidence Assessments—0
Improving Semi-Supervised Semantic Segmentation with Sliced-Wasserstein Feature Alignment and Uniformity—0
Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays—0
IPixMatch: Boost Semi-supervised Semantic Segmentation with Inter-Pixel Relation—0
Knowledge Consultation for Semi-Supervised Semantic Segmentation—0
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