{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/cinic-10-is-not-imagenet-or-cifar-10","title":"CINIC-10 is not ImageNet or CIFAR-10","arxiv_id":"1810.03505","date":"2018-10-02","proceeding":null,"authors":["Luke N. Darlow","Elliot J. Crowley","Antreas Antoniou","Amos J. Storkey"],"abstract":"In this brief technical report we introduce the CINIC-10 dataset as a plug-in\nextended alternative for CIFAR-10. It was compiled by combining CIFAR-10 with\nimages selected and downsampled from the ImageNet database. We present the\napproach to compiling the dataset, illustrate the example images for different\nclasses, give pixel distributions for each part of the repository, and give\nsome standard benchmarks for well known models. Details for download, usage,\nand compilation can be found in the associated github repository.","url_abs":"http://arxiv.org/abs/1810.03505v1","url_pdf":"http://arxiv.org/pdf/1810.03505v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"cinic-10-is-not-imagenet-or-cifar-10","repo_url":"https://github.com/BayesWatch/cinic-10","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"cinic-10-is-not-imagenet-or-cifar-10","repo_url":"https://github.com/2024-MindSpore-1/Code6/tree/main/AVA_cifar","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"mindspore","reach":null}],"tasks":[{"task_slug":"image-classification","task_name":"Image Classification"}],"methods":[{"method_slug":"1x1-convolution","method_name":"1x1 Convolution"},{"method_slug":"average-pooling","method_name":"Average Pooling"},{"method_slug":"batch-normalization","method_name":"Batch Normalization"},{"method_slug":"bottleneck-residual-block","method_name":"Bottleneck Residual Block"},{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"global-average-pooling","method_name":"Global Average Pooling"},{"method_slug":"grouped-convolution","method_name":"Grouped Convolution"},{"method_slug":"kaiming-initialization","method_name":"Kaiming Initialization"},{"method_slug":"max-pooling","method_name":"Max Pooling"},{"method_slug":"relu","method_name":"ReLU"},{"method_slug":"resnext","method_name":"ResNeXt"},{"method_slug":"resnext-block","method_name":"ResNeXt Block"},{"method_slug":"residual-block","method_name":"Residual Block"},{"method_slug":"residual-connection","method_name":"Residual Connection"}],"datasets_introduced":[{"slug":"cinic-10","name":"CINIC-10","full_name":"CINIC-10"}],"methods_introduced":[],"results":[{"leaderboard":"/sota/image-classification-on-cinic-10","task":"Image Classification","dataset":"CINIC-10","model":"ResNeXt29_2x64d","rank_in_archive_order":6,"of":9,"metrics":{"Accuracy":"91.45"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-cinic-10","task":"Image Classification","dataset":"CINIC-10","model":"DenseNet-121","rank_in_archive_order":7,"of":9,"metrics":{"Accuracy":"91.26"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-cinic-10","task":"Image Classification","dataset":"CINIC-10","model":"ResNet-18","rank_in_archive_order":8,"of":9,"metrics":{"Accuracy":"90.27"},"uses_additional_data":false},{"leaderboard":"/sota/image-classification-on-cinic-10","task":"Image Classification","dataset":"CINIC-10","model":"VGG-16","rank_in_archive_order":9,"of":9,"metrics":{"Accuracy":"87.77"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1810.03505","atlas_url":"https://app.syntology.ai/?focus=1810.03505","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}