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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 151–190 of 190 papers

TitleStatusHype
Fuzzy Positive Learning for Semi-supervised Semantic Segmentation—0
Pixel Contrastive-Consistent Semi-Supervised Semantic Segmentation—0
PRCL: Probabilistic Representation Contrastive Learning for Semi-Supervised Semantic Segmentation—0
Progressive Learning with Cross-Window Consistency for Semi-Supervised Semantic Segmentation—0
Reference-guided Pseudo-Label Generation for Medical Semantic Segmentation—0
Region-level Contrastive and Consistency Learning for Semi-Supervised Semantic Segmentation—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi-Supervised Semantic Segmentation—0
Revisiting Dilated Convolution: A Simple Approach for Weakly- and Semi- Supervised Semantic Segmentation—0
Revisiting Image Reconstruction for Semi-supervised Semantic Segmentation—0
Robust Mutual Learning for Semi-supervised Semantic Segmentation—0
S4-Net: Geometry-Consistent Semi-Supervised Semantic Segmentation—0
SAMST: A Transformer framework based on SAM pseudo label filtering for remote sensing semi-supervised semantic segmentation—0
Superpoint-guided Semi-supervised Semantic Segmentation of 3D Point Clouds—0
Semi-Supervised Building Footprint Generation with Feature and Output Consistency Training—0
Semi-Supervised Semantic Segmentation Based on Pseudo-Labels: A Survey—0
Semi-Supervised Semantic Segmentation in Earth Observation: The MiniFrance Suite, Dataset Analysis and Multi-task Network Study—0
Semi-supervised Semantic Segmentation Meets Masked Modeling:Fine-grained Locality Learning Matters in Consistency Regularization—0
Semi-Supervised Semantic Segmentation Methods for UW-OCTA Diabetic Retinopathy Grade Assessment—0
Semi-supervised semantic segmentation needs strong, high-dimensional perturbations—0
Semi-supervised Semantic Segmentation of Prostate and Organs-at-Risk on 3D Pelvic CT Images—0
Semi-Supervised Semantic Segmentation of Vessel Images using Leaking Perturbations—0
Semi-Supervised Semantic Segmentation of Cell Nuclei via Diffusion-based Large-Scale Pre-Training and Collaborative Learning—0
Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups—0
Semi Supervised Semantic Segmentation Using Generative Adversarial Network—0
Semi-supervised Semantic Segmentation using Auxiliary Network—0
Semi-Supervised Semantic Segmentation using Redesigned Self-Training for White Blood Cells—0
Semi-supervised Semantic Segmentation via Strong-weak Dual-branch Network—0
Semi-supervised Semantic Segmentation via Boosting Uncertainty on Unlabeled Data—0
Exploiting Minority Pseudo-Labels for Semi-Supervised Semantic Segmentation in Autonomous Driving—0
Simpler Does It: Generating Semantic Labels with Objectness Guidance—0
Space Engage: Collaborative Space Supervision for Contrastive-based Semi-Supervised Semantic Segmentation—0
Structured Consistency Loss for semi-supervised semantic segmentation—0
The GIST and RIST of Iterative Self-Training for Semi-Supervised Segmentation—0
Transferable Semi-supervised Semantic Segmentation—0
Transformer-CNN Cohort: Semi-supervised Semantic Segmentation by the Best of Both Students—0
Triple-View Knowledge Distillation for Semi-Supervised Semantic Segmentation—0
TrueDeep: A systematic approach of crack detection with less data—0
Uncertainty and Energy based Loss Guided Semi-Supervised Semantic Segmentation—0
What Can be Seen is What You Get: Structure Aware Point Cloud Augmentation—0
Zero-Shot Pseudo Labels Generation Using SAM and CLIP for Semi-Supervised Semantic Segmentation—0
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