CIFAR-10

Introduced by Krizhevsky et al. in Learning multiple layers of features from tiny images

The CIFAR-10 dataset (Canadian Institute for Advanced Research, 10 classes) is a subset of the Tiny Images dataset and consists of 60000 32x32 color images. The images are labelled with one of 10 mutually exclusive classes: airplane, automobile (but not truck or pickup truck), bird, cat, deer, dog, frog, horse, ship, and truck (but not pickup truck). There are 6000 images per class with 5000 training and 1000 testing images per class.

Task	Dataset Variant	Best Model
Image Classification	CIFAR-10	ViT-H/14
Image Generation	CIFAR-10	EDM-G++
Long-tail Learning	CIFAR-10-LT (ρ=10)	GLMC+MaxNorm
Semi-Supervised Image Classification	CIFAR-10, 4000 Labels	SemCo
Neural Architecture Search	CIFAR-10	NAT-M4
Anomaly Detection	One-class CIFAR-10	CLIP
Image Clustering	CIFAR-10	SPICE*
Conditional Image Generation	CIFAR-10	EDM-G++
Semi-Supervised Image Classification	CIFAR-10, 250 Labels	Dash
Long-tail Learning	CIFAR-10-LT (ρ=100)	GLMC+MaxNorm
Neural Architecture Search	CIFAR-10 Image Classification	NAT-M4
Semi-Supervised Image Classification	CIFAR-10, 40 Labels	FreeMatch
Out-of-Distribution Detection	CIFAR-100 vs CIFAR-10	DHM
Out-of-Distribution Detection	CIFAR-10 vs CIFAR-100	DHM
Graph Classification	CIFAR10 100k	Exphormer
Anomaly Detection	Unlabeled CIFAR-10 vs CIFAR-100	PsudoLabels ViT
Image Classification	cifar10	BEiT-finetuned
Out-of-Distribution Detection	CIFAR-10	DHM
Semi-Supervised Image Classification	CIFAR-10, 1000 Labels	MixMatch
Sequential Image Classification	noise padded CIFAR-10	FlexTCN-6
Personalized Federated Learning	CIFAR-10	pFedHN-PC
Stochastic Optimization	CIFAR-10 WRN-28-10 - 200 Epochs	Adam
Adversarial Defense	CIFAR-10	WRN-28-10
Small Data Image Classification	CIFAR-10, 500 Labels	ChimeraMix+AutoAugment
Stochastic Optimization	CIFAR-100 WRN-28-10 - 200 Epochs	AvaGrad
Classification with Binary Weight Network	CIFAR-10	WRN-28-10
Sparse Learning and binarization	CIFAR-10	SBNN-50%
Unsupervised Anomaly Detection with Specified Settings -- 20% anomaly	cifar10	Shell-Renormalized
Unsupervised Anomaly Detection with Specified Settings -- 30% anomaly	CIFAR-10	Shell-Renormalized
Unsupervised Anomaly Detection with Specified Settings -- 0.1% anomaly	CIFAR-10	LVAD
Unsupervised Anomaly Detection with Specified Settings -- 1% anomaly	CIFAR-10	LVAD
Unsupervised Anomaly Detection with Specified Settings -- 10% anomaly	CIFAR-10	LVAD
Small Data Image Classification	CIFAR-10, 1000 Labels	ChimeraMix+AutoAugment
Neural Network Compression	CIFAR-10	ShuffleNet – Quantised
Data Augmentation	CIFAR-10	Shake-Shake
Network Pruning	CIFAR-10	TAS-pruned ResNet-110
Semi-Supervised Image Classification	cifar10, 250 Labels	ReMixMatch
Stochastic Optimization	CIFAR-10 ResNet-18 - 200 Epochs	SGD - cosine LR schedule
Image Classification	CIFAR-10 (with noisy labels)	SSR
Unsupervised Image Classification	CIFAR-10	RUC
Open-World Semi-Supervised Learning	CIFAR-10	OpenLDN
Density Estimation	CIFAR-10	MAF
Semi-Supervised Image Classification	CIFAR-10, 2000 Labels	MixMatch
Clean-label Backdoor Attack (0.05%)	CIFAR-10	GoogLeNet
Robust classification	CIFAR-10	ResNet-44 w/ Robust Loss, Adv. Training, and HHReLU
Semi-Supervised Image Classification	CIFAR-10, 20 Labels	MutexMatch
Adversarial Attack	CIFAR-10	Xu et al.
Classification with Binary Neural Network	CIFAR-10	AdaBin
Binarization	CIFAR-10	WRN-28-10
Small Data Image Classification	cifar10, 10 labels	VAE
Image Classification	CIFAR-10 Image Classification	ASF-former-S
Semi-Supervised Image Classification	CIFAR-10, 80 Labels	MutexMatch
Nature-Inspired Optimization Algorithm	CIFAR-10	Position-wise optimizer
Adversarial Robustness	CIFAR-10	Stochastic-LWTA/PGD/WideResNet-34-10
Quantization	CIFAR-10	3DCNN_VIVA_3
Stochastic Optimization	CIFAR-10	Resnet18
Anomaly Detection	CIFAR-10	RCALAD
Image Classification	cifar-10,4000	WRN-28-2 + UDA+AutoDropout
Hard-label Attack	CIFAR-10	RayS
Semi-Supervised Image Classification (Cold Start)	CIFAR-10, 40 Labels	FixMatch-USL-T
Image Compression	CIFAR-10	Lossyless Compressor
Density Estimation	CIFAR-10 (Conditional)	MAF
Image Classification	CIFAR10_CATS	CatsNet
Model Poisoning	CIFAR-10	ADA
Image Retrieval	CIFAR-10	Custom: 3 conv + 2 fcn
Image Classification with Label Noise	CIFAR-10	PropMix
Semi-Supervised Image Classification	CIFAR-10, 500 Labels	MixMatch
Out-of-Distribution Detection	cifar10	Wideresnet 40
Novel Class Discovery	cifar10	NCL
Learning with noisy labels	CIFAR-10	ILL
Long-tail Learning on CIFAR-10-LT (ρ=100)	CIFAR-10-LT (ρ=100)	BCL
Small Data Image Classification	CIFAR-10, 250 Labels	GLICO

CIFAR-10

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