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Pseudo Label

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A lightweight but very power technique for semi supervised learning

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/microsoft/SoftTeacher

공식 코드

End-to-End Semi-Supervised Object Detection with Soft Teacher

https://github.com/milkxie/ssmll-cap

공식 코드

Class-Distribution-Aware Pseudo Labeling for Semi-Supervised Multi-Label Learning

https://github.com/mingukjang/tast

공식 코드

Test-Time Adaptation via Self-Training with Nearest Neighbor Information

https://github.com/mlspeech/gradseg

공식 코드

Unsupervised Word Segmentation Using Temporal Gradient Pseudo-Labels

https://github.com/moucheng2017/emssl

공식 코드

Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-Supervised Segmentation

https://github.com/movinghoon/mira

공식 코드

Unsupervised Visual Representation Learning via Mutual Information Regularized Assignment

https://github.com/mu-y/mpl-mdd

공식 코드

Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment

https://github.com/mxahan/nev-ncd

공식 코드

Novel Categories Discovery Via Constraints on Empirical Prediction Statistics

https://github.com/mxbh/spatiotemporal-ssl

공식 코드

Context Matters: Leveraging Spatiotemporal Metadata for Semi-Supervised Learning on Remote Sensing Images

https://github.com/nayeemrizve/trssl

공식 코드

Towards Realistic Semi-Supervised Learning

https://github.com/nayeemrizve/ups

공식 코드

In Defense of Pseudo-Labeling: An Uncertainty-Aware Pseudo-label Selection Framework for Semi-Supervised Learning

https://github.com/nazmul-karim170/C-SFDA_Source-Free-Domain-Adaptation

공식 코드

C-SFDA: A Curriculum Learning Aided Self-Training Framework for Efficient Source Free Domain Adaptation

https://github.com/nhcha6/classdistributionprediction

공식 코드

Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection

https://github.com/niamhbelton/ss-fewsome_disease_severity_knee_osteoarthritis

공식 코드

An AI System for Continuous Knee Osteoarthritis Severity Grading Using Self-Supervised Anomaly Detection with Limited Data

https://github.com/nini0919/semires

공식 코드

SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation

https://github.com/nini0919/sspng

공식 코드

Semi-Supervised Panoptic Narrative Grounding

https://github.com/nust-machine-intelligence-laboratory/i2crc

공식 코드

Saliency Guided Inter- and Intra-Class Relation Constraints for Weakly Supervised Semantic Segmentation

https://github.com/nust-machine-intelligence-laboratory/torchsemiseg2

공식 코드

Semi-Supervised Semantic Segmentation With Region Relevance

https://github.com/oiplab-dut/mfnet

공식 코드

MFNet: Multi-filter Directive Network for Weakly Supervised Salient Object Detection

https://github.com/open-mmlab/OpenSelfSup

공식 코드

Delving into Inter-Image Invariance for Unsupervised Visual Representations

https://github.com/open-mmlab/mmselfsup

공식 코드

Delving into Inter-Image Invariance for Unsupervised Visual Representations

https://github.com/ortonwang/plgdf

공식 코드

Pseudo Label-Guided Data Fusion and Output Consistency for Semi-Supervised Medical Image Segmentation

https://github.com/ortonwang/scribblevs

공식 코드

ScribbleVS: Scribble-Supervised Medical Image Segmentation via Dynamic Competitive Pseudo Label Selection

https://github.com/osmanberke/sfda-ssvep-bci

공식 코드

Source-Free Domain Adaptation for SSVEP-based Brain-Computer Interfaces

https://github.com/p-karisani/self_pretraining

공식 코드

Semi-Supervised Text Classification via Self-Pretraining

https://github.com/pascalschlachter/planalysis

공식 코드

Analysis of Pseudo-Labeling for Online Source-Free Universal Domain Adaptation

https://github.com/paulalbert31/pls

공식 코드

Is your noise correction noisy? PLS: Robustness to label noise with two stage detection

https://github.com/paulalbert31/sncf

공식 코드

Is your noise correction noisy? PLS: Robustness to label noise with two stage detection

https://github.com/pixel-333/MRCMV

공식 코드

Deep Music Retrieval for Fine-Grained Videos by Exploiting Cross-Modal-Encoded Voice-Overs

https://github.com/pphub-hy/torch-tapnet

공식 코드

Deep Learning based Intelligent Coin-tap Test for Defect Recognition

https://github.com/prantikbubun/beyond-pixels

공식 코드

Beyond Pixels: Semi-Supervised Semantic Segmentation with a Multi-scale Patch-based Multi-Label Classifier

https://github.com/puchapu/utep

공식 코드

Learning Unbiased Transferability for Domain Adaptation by Uncertainty Modeling

https://github.com/qdin4048/CPL-OT

공식 코드

Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignment

https://github.com/qiumuyang/siab

공식 코드

The Devil is in the Statistics: Mitigating and Exploiting Statistics Difference for Generalizable Semi-supervised Medical Image Segmentation

https://github.com/qiurui4shu/PIG

공식 코드

PIG: Prompt Images Guidance for Night-Time Scene Parsing

https://github.com/reactivetype/simrod

공식 코드

SimROD: A Simple Adaptation Method for Robust Object Detection

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