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Pseudo Label

A lightweight but very power technique for semi supervised learning

Papers

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Showing 351–375 of 956 papers

TitleStatusHype
Mixed Pseudo Labels for Semi-Supervised Object DetectionCode1
Semi-supervised Active Learning for Video Action DetectionCode0
RankMatch: A Novel Approach to Semi-Supervised Label Distribution Learning Leveraging Inter-label Correlations—0
Two-Stage Adaptive Network for Semi-Supervised Cross-Domain Crater Detection under Varying Scenario Distributions—0
Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised AdaptationCode1
Diffusion-SS3D: Diffusion Model for Semi-supervised 3D Object DetectionCode1
Enhancing and Adapting in the Clinic: Source-free Unsupervised Domain Adaptation for Medical Image EnhancementCode1
Learning Part Segmentation from Synthetic Animals—0
Turn Down the Noise: Leveraging Diffusion Models for Test-time Adaptation via Pseudo-label Ensembling—0
Language-conditioned Detection TransformerCode1
Pseudo-label Correction for Instance-dependent Noise Using Teacher-student Framework—0
Large Language Models as Topological Structure Enhancers for Text-Attributed Graphs—0
Density-Guided Dense Pseudo Label Selection For Semi-supervised Oriented Object DetectionCode0
SSASS: Semi-Supervised Approach for Stenosis Segmentation—0
Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image SegmentationCode0
Gradual Source Domain Expansion for Unsupervised Domain AdaptationCode1
SCADI: Self-supervised Causal Disentanglement in Latent Variable ModelsCode0
FireMatch: A Semi-Supervised Video Fire Detection Network Based on Consistency and Distribution Alignment—0
Generating Unbiased Pseudo-labels via a Theoretically Guaranteed Chebyshev Constraint to Unify Semi-supervised Classification and RegressionCode0
Towards Generalized Multi-stage Clustering: Multi-view Self-distillation—0
Optimization-Free Test-Time Adaptation for Cross-Person Activity RecognitionCode1
Self-Supervised Multi-Modality Learning for Multi-Label Skin Lesion ClassificationCode0
M3C: A Framework towards Convergent, Flexible, and Unsupervised Learning of Mixture Graph Matching and Clustering—0
Semi-Supervised Panoptic Narrative GroundingCode1
Navigating Data Heterogeneity in Federated Learning A Semi-Supervised Federated Object DetectionCode1
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