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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 26–50 of 190 papers

TitleStatusHype
Augmentation Matters: A Simple-yet-Effective Approach to Semi-supervised Semantic SegmentationCode1
Robust Semantic Segmentation with Superpixel-MixCode1
Conflict-Based Cross-View Consistency for Semi-Supervised Semantic SegmentationCode1
Less is More: Reducing Task and Model Complexity for 3D Point Cloud Semantic SegmentationCode1
Conservative-Progressive Collaborative Learning for Semi-supervised Semantic SegmentationCode1
Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic SegmentationCode1
Missing Modality Robustness in Semi-Supervised Multi-Modal Semantic SegmentationCode1
Boosting Semi-Supervised Semantic Segmentation with Probabilistic RepresentationsCode1
Co-training with High-Confidence Pseudo Labels for Semi-supervised Medical Image SegmentationCode1
Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR SegmentationCode1
Bootstrapping Semantic Segmentation with Regional ContrastCode1
FIDNet: LiDAR Point Cloud Semantic Segmentation with Fully Interpolation DecodingCode1
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning resultsCode1
A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data AugmentationCode1
Hunting Sparsity: Density-Guided Contrastive Learning for Semi-Supervised Semantic SegmentationCode1
NP-SemiSeg: When Neural Processes meet Semi-Supervised Semantic SegmentationCode1
Part-aware Prototype Network for Few-shot Semantic SegmentationCode1
Adversarial Dual-Student with Differentiable Spatial Warping for Semi-Supervised Semantic SegmentationCode1
Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth EstimationCode1
CorrMatch: Label Propagation via Correlation Matching for Semi-Supervised Semantic SegmentationCode1
CauSSL: Causality-inspired Semi-supervised Learning for Medical Image SegmentationCode1
Semi-supervised semantic segmentation needs strong, varied perturbationsCode1
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic SegmentationCode1
ClassMix: Segmentation-Based Data Augmentation for Semi-Supervised LearningCode1
Inconsistency Masks: Removing the Uncertainty from Input-Pseudo-Label PairsCode1
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