Papers with Code 아카이브

Semi-Supervised Image Classification

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하위 태스크: 2
평가표: 59
보존된 평가 기록: 456

Semi-supervised image classification leverages unlabelled data as well as labelled data to increase classification performance.

You may want to read some blog posts to get an overview before reading the papers and checking the leaderboards:

An overview of proxy-label approaches for semi-supervised learning - Sebastian Ruder
Semi-Supervised Learning in Computer Vision - Amit Chaudhary

<span style="color:grey; opacity: 0.6">( Image credit: Self-Supervised Semi-Supervised Learning )</span>

코드

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

https://github.com/ljjcoder/probabilistic-contrastive-learning

공식 코드

Probabilistic Contrastive Learning for Domain Adaptation

https://github.com/lnsmith54/BOSS

공식 코드

Building One-Shot Semi-supervised (BOSS) Learning up to Fully Supervised Performance

https://github.com/maciejczyzewski/batchboost

공식 코드

batchboost: regularization for stabilizing training with resistance to underfitting & overfitting

https://github.com/mahdiabavisani/DSRC

공식 코드

Deep Sparse Representation-based Classification

https://github.com/maple-research-lab/EnAET

공식 코드

EnAET: A Self-Trained framework for Semi-Supervised and Supervised Learning with Ensemble Transformations

https://github.com/microsoft/react

공식 코드

Learning Customized Visual Models with Retrieval-Augmented Knowledge

https://github.com/microsoft/semi-supervised-learning

공식 코드

FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning

https://github.com/mingkai-zheng/simmatchv2

공식 코드

SimMatchV2: Semi-Supervised Learning with Graph Consistency

https://github.com/miquelmarti/DenseFixMatch

공식 코드

An analysis of over-sampling labeled data in semi-supervised learning with FixMatch

https://github.com/nayeemrizve/openldn

공식 코드

OpenLDN: Learning to Discover Novel Classes for Open-World Semi-Supervised Learning

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/niusj03/owmatch

공식 코드

OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning

https://github.com/njustkmg/ssoc

공식 코드

Robust Semi-Supervised Learning for Self-learning Open-World Classes

https://github.com/njuyued/prg4ssl-mnar

공식 코드

Towards Semi-supervised Learning with Non-random Missing Labels

https://github.com/njuyued/rda4robustssl

공식 코드

RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning

https://github.com/njuyued/soc4ss-fgvc

공식 코드

Roll With the Punches: Expansion and Shrinkage of Soft Label Selection for Semi-supervised Fine-Grained Learning

https://github.com/openai/CLIP

공식 코드

Learning Transferable Visual Models From Natural Language Supervision

https://github.com/openai/improved-gan

공식 코드

Improved Techniques for Training GANs

https://github.com/openai/improved_gan

공식 코드

Improved Techniques for Training GANs

https://github.com/psellcam/LaplaceNet

공식 코드

LaplaceNet: A Hybrid Graph-Energy Neural Network for Deep Semi-Supervised Classification

https://github.com/qinenergy/adanet

공식 코드

Semi-Supervised Learning by Augmented Distribution Alignment

https://github.com/rahul13ramesh/deep_reference_priors

공식 코드

Deep Reference Priors: What is the best way to pretrain a model?

https://github.com/ruckbreasoning/openima

공식 코드

Open-World Semi-Supervised Learning for Node Classification

https://github.com/salesforce/CoMatch

공식 코드

CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

https://github.com/salesforce/PCL

공식 코드

Prototypical Contrastive Learning of Unsupervised Representations

https://github.com/sgvaze/generalized-category-discovery

공식 코드

Generalized Category Discovery

https://github.com/shuvenduroy/unmixmatch

공식 코드

Scaling Up Semi-supervised Learning with Unconstrained Unlabelled Data

https://github.com/smlaine2/tempens

공식 코드

Temporal Ensembling for Semi-Supervised Learning

https://github.com/snap-stanford/orca

공식 코드

Open-World Semi-Supervised Learning

https://github.com/takerum/vat_chainer

공식 코드

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

https://github.com/takerum/vat_tf

공식 코드

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

https://github.com/taufikxu/Triple-GAN

공식 코드

Triple Generative Adversarial Networks

https://github.com/tencentyouturesearch/classification-semicls

공식 코드

Class-Aware Contrastive Semi-Supervised Learning

https://github.com/thudzj/StructuredGAN

공식 코드

Structured Generative Adversarial Networks

https://github.com/thuml/debiased-self-training

공식 코드

Debiased Self-Training for Semi-Supervised Learning

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