CINIC-10 is not ImageNet or CIFAR-10

Luke N. Darlow, Elliot J. Crowley, Antreas Antoniou, Amos J. Storkey

2018-10-02Image Classification

Abstract

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.

Results

Task	Dataset	Metric	Value	Model
Image Classification	CINIC-10	Accuracy	91.45	ResNeXt29_2x64d
Image Classification	CINIC-10	Accuracy	91.26	DenseNet-121
Image Classification	CINIC-10	Accuracy	90.27	ResNet-18
Image Classification	CINIC-10	Accuracy	87.77	VGG-16

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