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 26–50 of 167 papers

Title	Date	Tasks	Status	Hype
NP-Match: Towards a New Probabilistic Model for Semi-Supervised Learning	Jan 31, 2023	Classificationimage-classification	CodeCode Available	1
Learning Customized Visual Models with Retrieval-Augmented Knowledge	Jan 17, 2023	Contrastive LearningRetrieval	CodeCode Available	1
Semi-MAE: Masked Autoencoders for Semi-supervised Vision Transformers	Jan 4, 2023	Decoderimage-classification	—Unverified	0
Self Meta Pseudo Labels: Meta Pseudo Labels Without The Teacher	Dec 27, 2022	Semi-Supervised Image Classification	—Unverified	0
Beyond ADMM: A Unified Client-variance-reduced Adaptive Federated Learning Framework	Dec 3, 2022	Federated Learningimage-classification	—Unverified	0
SVFormer: Semi-supervised Video Transformer for Action Recognition	Nov 23, 2022	Action Recognitionimage-classification	CodeCode Available	1
Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors	Sep 30, 2022	3D Reconstructionimage-classification	CodeCode Available	1
OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning	Sep 11, 2022	BenchmarkingClassification	CodeCode Available	0
USB: A Unified Semi-supervised Learning Benchmark for Classification	Aug 12, 2022	General ClassificationGPU	CodeCode Available	3
Semi-supervised Vision Transformers at Scale	Aug 11, 2022	Inductive BiasSemi-Supervised Image Classification	CodeCode Available	1
RDA: Reciprocal Distribution Alignment for Robust Semi-supervised Learning	Aug 9, 2022	Semi-Supervised Image Classification	CodeCode Available	0
Semi-Supervised Hyperspectral Image Classification Using a Probabilistic Pseudo-Label Generation Framework	Aug 5, 2022	Hyperspectral Image Classificationimage-classification	CodeCode Available	1
NP-Match: When Neural Processes meet Semi-Supervised Learning	Jul 3, 2022	image-classificationImage Classification	CodeCode Available	1
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning	May 15, 2022	FairnessSemi-Supervised Image Classification	CodeCode Available	3
DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision	May 11, 2022	Semi-Supervised Image Classification	CodeCode Available	0
Masked Siamese Networks for Label-Efficient Learning	Apr 14, 2022	image-classificationImage Classification	CodeCode Available	2
MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization	Mar 27, 2022	Semi-Supervised Image Classification	CodeCode Available	1
SimMatch: Semi-supervised Learning with Similarity Matching	Mar 14, 2022	Semantic SimilaritySemantic Textual Similarity	CodeCode Available	0
Class-Aware Contrastive Semi-Supervised Learning	Mar 4, 2022	Image ClassificationPseudo Label	CodeCode Available	1
Global-Local Regularization Via Distributional Robustness	Mar 1, 2022	Adversarial RobustnessDomain Adaptation	CodeCode Available	0
Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision	Feb 16, 2022	Action ClassificationAction Recognition	CodeCode Available	0
Debiased Self-Training for Semi-Supervised Learning	Feb 15, 2022	Object RecognitionScene Classification	CodeCode Available	1
Deep Reference Priors: What is the best way to pretrain a model?	Feb 1, 2022	image-classificationSemi-Supervised Image Classification	CodeCode Available	0
Contrastive Regularization for Semi-Supervised Learning	Jan 17, 2022	Semi-Supervised Image Classification	—Unverified	0
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?	Jan 13, 2022	image-classificationImage Classification	CodeCode Available	0

Show:10 25 50

← PrevPage 2 of 7Next →

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	Semi-SST (ViT-Huge)	Top 1 Accuracy	80.7	—	Unverified
6	Meta Co-Training	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