Semi-Supervised Image Classification

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

( Image credit: Self-Supervised Semi-Supervised Learning )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 121–130 of 167 papers

Title	Date	Tasks	Status	Score
Triple Generative Adversarial Networks	Dec 20, 2019	ClassificationConditional Image Generation	CodeCode Available	5
Two Methods for Domain Adaptation of Bilingual Tasks: Delightfully Simple and Broadly Applicable	Jul 1, 2018	Bilingual Lexicon InductionClassification	CodeCode Available	5
SequenceMatch: Revisiting the design of weak-strong augmentations for Semi-supervised learning	Oct 24, 2023	Semi-Supervised Image ClassificationSemi-Supervised Image Classification on ImageNet - 10% labeled data	CodeCode Available	5
One Shot Model For The Prediction of COVID-19 and Lesions Segmentation In Chest CT Scans Through The Affinity Among Lesion Mask Features	Jan 4, 2021	COVID-19 DiagnosisInstance Segmentation	CodeCode Available	5
Online Semi-Supervised Learning in Contextual Bandits with Episodic Reward	Sep 17, 2020	ClusteringDecision Making	CodeCode Available	5
ViTSGMM: A Robust Semi-Supervised Image Recognition Network Using Sparse Labels	Jun 4, 2025	Semi-Supervised Image Classification	CodeCode Available	5
SimMatch: Semi-supervised Learning with Similarity Matching	Mar 14, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	5
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision	Feb 16, 2022	Action ClassificationAction Recognition	—Unverified	0
10,000+ Times Accelerated Robust Subset Selection (ARSS)	Sep 12, 2014	10-shot image generationAction Recognition	—Unverified	0
LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching	Oct 13, 2020	Domain AdaptationSemi-Supervised Image Classification	—Unverified	0

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All datasets ImageNet - 10% labeled data ImageNet - 1% labeled data CIFAR-10, 4000 Labels cifar-100, 10000 Labels CIFAR-10, 250 Labels SVHN, 1000 labels SVHN, 250 Labels CIFAR-10, 40 Labels CIFAR-100, 400 Labels CIFAR-10, 1000 Labels CIFAR-100, 2500 Labels STL-10, 1000 Labels

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	SimCLR (ResNet-50 4×)	Top 5 Accuracy	92.6	—	Unverified
2	Rotation + VAT + Ent. Min.	Top 5 Accuracy	91.23	—	Unverified
3	SimCLR (ResNet-50 2×)	Top 5 Accuracy	91.2	—	Unverified
4	Mean Teacher (ResNeXt-152)	Top 5 Accuracy	90.89	—	Unverified
5	OBoW (ResNet-50)	Top 5 Accuracy	90.7	—	Unverified
6	R2-D2 (ResNet-18)	Top 5 Accuracy	90.48	—	Unverified
7	FixMatch	Top 5 Accuracy	89.13	—	Unverified
8	UDA	Top 5 Accuracy	88.52	—	Unverified
9	SimCLR (ResNet-50)	Top 5 Accuracy	87.8	—	Unverified
10	DHO (ViT-Large)	Top 1 Accuracy	85.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DHO (ViT-Large)	Top 1 Accuracy	84.6	—	Unverified
2	OBoW (ResNet-50)	Top 5 Accuracy	82.9	—	Unverified
3	DHO (ViT-Base)	Top 1 Accuracy	81.6	—	Unverified
4	REACT (ViT-Large)	Top 1 Accuracy	81.6	—	Unverified
5	Meta Co-Training	Top 1 Accuracy	80.7	—	Unverified
6	Semi-SST (ViT-Huge)	Top 1 Accuracy	80.7	—	Unverified
7	Super-SST (ViT-Huge)	Top 1 Accuracy	80.3	—	Unverified
8	Semi-ViT (ViT-Huge)	Top 1 Accuracy	80	—	Unverified
9	Semi-ViT (ViT-Large)	Top 1 Accuracy	77.3	—	Unverified
10	Super-SST (ViT-Small distilled)	Top 1 Accuracy	76.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Γ-model	Percentage error	20.4	—	Unverified
2	GAN	Percentage error	15.59	—	Unverified
3	Bad GAN	Percentage error	14.41	—	Unverified
4	Triple-GAN-V2 (CNN-13, no aug)	Percentage error	12.41	—	Unverified
5	Pi Model	Percentage error	12.16	—	Unverified
6	SESEMI SSL (ConvNet)	Percentage error	11.65	—	Unverified
7	VAT	Percentage error	11.36	—	Unverified
8	GLOT-DR	Percentage error	10.6	—	Unverified
9	VAT+EntMin	Percentage error	10.55	—	Unverified
10	Triple-GAN-V2 (CNN-13)	Percentage error	10.01	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Ⅱ-Model	Percentage error	39.19	—	Unverified
2	SESEMI SSL (ConvNet)	Percentage error	38.7	—	Unverified
3	Temporal ensembling	Percentage error	38.65	—	Unverified
4	R2-D2 (CNN-13)	Percentage error	32.87	—	Unverified
5	Dual Student (480)	Percentage error	32.77	—	Unverified
6	UPS (CNN-13)	Percentage error	32	—	Unverified
7	SHOT-VAE	Percentage error	25.3	—	Unverified
8	LiDAM	Percentage error	23.22	—	Unverified
9	EnAET (WRN-28-2-Large)	Percentage error	22.92	—	Unverified
10	FixMatch (RA, WRN-28-8)	Percentage error	22.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Ⅱ-Model	Percentage error	53.12	—	Unverified
2	MixUp	Percentage error	47.43	—	Unverified
3	MeanTeacher	Percentage error	47.32	—	Unverified
4	VAT	Percentage error	36.03	—	Unverified
5	LiDAM	Percentage error	19.17	—	Unverified
6	MixMatch	Percentage error	11.08	—	Unverified
7	RealMix	Percentage error	9.79	—	Unverified
8	EnAET	Percentage error	7.6	—	Unverified
9	ReMixMatch	Percentage error	6.27	—	Unverified
10	FixMatch+CR	Percentage error	5.04	—	Unverified