{"url":"/dataset/stylized-imagenet","name":"Stylized ImageNet","full_name":"Stylized ImageNet","description_markdown":"The Stylized-ImageNet dataset is created by removing local texture cues in ImageNet while retaining global shape information on natural images via AdaIN style transfer. This nudges CNNs towards learning more about shapes and less about local textures.\r\n\r\nSource: [Adversarial Examples Improve Image Recognition](https://arxiv.org/abs/1911.09665)\r\nImage Source: [https://github.com/rgeirhos/Stylized-ImageNet](https://github.com/rgeirhos/Stylized-ImageNet)","description_withheld":null,"homepage":"https://github.com/rgeirhos/Stylized-ImageNet","introduced_date":"2019-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/imagenet-trained-cnns-are-biased-towards","title":"ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness","first_author":"Robert Geirhos","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Domain Generalization","url":"/task/domain-generalization","datasets_with_task":"/datasets/task/domain-generalization"},{"name":"Adversarial Robustness","url":"/task/adversarial-robustness","datasets_with_task":"/datasets/task/adversarial-robustness"}],"languages":[],"variants":["Stylized ImageNet"],"data_loaders":[{"repo":"https://github.com/rgeirhos/Stylized-ImageNet","url":"https://github.com/rgeirhos/Stylized-ImageNet","frameworks":["pytorch"]}],"num_papers_in_archive":106,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/adversarial-robustness-on-stylized-imagenet","task":"Adversarial Robustness","dataset_variant":"Stylized ImageNet","rows":4,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"DeiT-S (AdamW, Cosine)","paper":"/paper/are-transformers-more-robust-than-cnns","metrics":{"Accuracy":"13.0"},"code_links":[{"title":"ytongbai/ViTs-vs-CNNs","url":"https://github.com/ytongbai/ViTs-vs-CNNs"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/are-transformers-more-robust-than-cnns","title":"Are Transformers More Robust Than CNNs?","date":"2021-11-10","rows_on_this_dataset":4,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}