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Pseudo Label

A lightweight but very power technique for semi supervised learning

Papers

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Showing 51–75 of 956 papers

TitleStatusHype
Feature Modulation for Semi-Supervised Domain Generalization without Domain Labels—0
Semi-supervised Node Importance Estimation with Informative Distribution Modeling for Uncertainty RegularizationCode0
Building Blocks for Robust and Effective Semi-Supervised Real-World Object Detection—0
Adapt, Agree, Aggregate: Semi-Supervised Ensemble Labeling for Graph Convolutional Networks—0
Generalized Few-shot 3D Point Cloud Segmentation with Vision-Language ModelCode2
Enhancing Close-up Novel View Synthesis via Pseudo-labelingCode1
Multi-label feature selection based on binary hashing learning and dynamic graph constraints—0
Boosting Semi-Supervised Medical Image Segmentation via Masked Image Consistency and Discrepancy Learning—0
Mind the Gap: Confidence Discrepancy Can Guide Federated Semi-Supervised Learning Across Pseudo-MismatchCode1
MonoCT: Overcoming Monocular 3D Detection Domain Shift with Consistent Teacher Models—0
BFANet: Revisiting 3D Semantic Segmentation with Boundary Feature AnalysisCode1
Revisiting semi-supervised learning in the era of foundation modelsCode1
OmniSAM: Omnidirectional Segment Anything Model for UDA in Panoramic Semantic Segmentation—0
SP3D: Boosting Sparsely-Supervised 3D Object Detection via Accurate Cross-Modal Semantic PromptsCode1
STiL: Semi-supervised Tabular-Image Learning for Comprehensive Task-Relevant Information Exploration in Multimodal ClassificationCode1
Semi-Supervised Learning for Dose Prediction in Targeted Radionuclide: A Synthetic Data Study—0
ClipGrader: Leveraging Vision-Language Models for Robust Label Quality Assessment in Object Detection—0
You Only Click Once: Single Point Weakly Supervised 3D Instance Segmentation for Autonomous Driving—0
Distill Any Depth: Distillation Creates a Stronger Monocular Depth EstimatorCode4
CLIMB-3D: Continual Learning for Imbalanced 3D Instance SegmentationCode0
BP-SGCN: Behavioral Pseudo-Label Informed Sparse Graph Convolution Network for Pedestrian and Heterogeneous Trajectory PredictionCode0
Learning Wall Segmentation in 3D Vessel Trees using Sparse Annotations—0
Leveraging Labelled Data Knowledge: A Cooperative Rectification Learning Network for Semi-supervised 3D Medical Image SegmentationCode1
Without Paired Labeled Data: An End-to-End Self-Supervised Paradigm for UAV-View Geo-LocalizationCode2
Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression—0
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