TASK	DATASET	MODEL	METRIC NAME	METRIC VALUE	GLOBAL RANK
Image Classification	CINIC-10	ResNeXt29_2x64d	Accuracy	91.45	# 6
Image Classification	CINIC-10	VGG-16	Accuracy	87.77	# 9
Image Classification	CINIC-10	ResNet-18	Accuracy	90.27	# 8
Image Classification	CINIC-10	DenseNet-121	Accuracy	91.26	# 7

Badge	Markdown
	`[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/cinic-10-is-not-imagenet-or-cifar-10/image-classification-on-cinic-10)](https://paperswithcode.com/sota/image-classification-on-cinic-10?p=cinic-10-is-not-imagenet-or-cifar-10)`

CINIC-10 is not ImageNet or CIFAR-10

2 Oct 2018 · Luke N. Darlow, Elliot J. Crowley, Antreas Antoniou, Amos J. Storkey ·

In this brief technical report we introduce the CINIC-10 dataset as a plug-in extended alternative for CIFAR-10. It was compiled by combining CIFAR-10 with images selected and downsampled from the ImageNet database. We present the approach to compiling the dataset, illustrate the example images for different classes, give pixel distributions for each part of the repository, and give some standard benchmarks for well known models. Details for download, usage, and compilation can be found in the associated github repository.

PDF Abstract

Code

Add Remove Mark official

BayesWatch/cinic-10 official

231

2024-MindSpore-1/Code6

Tasks

Add Remove

Image Classification

Datasets

Introduced in the Paper:

CINIC-10

Used in the Paper:

CIFAR-10

CIFAR-100

ImageNet-32

Results from the Paper

Edit

Ranked #6 on Image Classification on CINIC-10

Get a GitHub badge

Task	Dataset	Model	Metric Name	Metric Value	Global Rank	Benchmark
Image Classification	CINIC-10	ResNeXt29_2x64d	Accuracy	91.45	# 6	Compare
Image Classification	CINIC-10	VGG-16	Accuracy	87.77	# 9	Compare
Image Classification	CINIC-10	ResNet-18	Accuracy	90.27	# 8	Compare
Image Classification	CINIC-10	DenseNet-121	Accuracy	91.26	# 7	Compare

Methods

Add Remove

1x1 Convolution • Average Pooling • Batch Normalization • Bottleneck Residual Block • Convolution • Global Average Pooling • Grouped Convolution • Kaiming Initialization • Max Pooling • ReLU • Residual Block • Residual Connection • ResNet • ResNeXt • ResNeXt Block

Edit Social Preview

CINIC-10 is not ImageNet or CIFAR-10

Code Edit Add Remove Mark official

Tasks Edit Add Remove

Datasets Edit

Results from the Paper Edit

Methods Edit Add Remove

Code

Add Remove Mark official

Tasks

Add Remove

Datasets

Results from the Paper

Edit

Methods

Add Remove