{"url":"/dataset/cats-vs-dogs","name":"Cats and Dogs","full_name":null,"description_markdown":"A large set of images of cats and dogs. \r\n\r\nHomepage: https://www.microsoft.com/en-us/download/details.aspx?id=54765\r\n\r\nSource code: tfds.image_classification.CatsVsDogs\r\n\r\nVersions:\r\n\r\n4.0.0 (default): New split API (https://tensorflow.org/datasets/splits)\r\nDownload size: 786.68 MiB\r\n\r\n\r\nSource: https://www.tensorflow.org/datasets/catalog/cats_vs_dogs","description_withheld":null,"homepage":"https://www.microsoft.com/en-us/download/details.aspx?id=54765","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"Unsupervised Anomaly Detection with Specified Settings -- 20% anomaly","url":"/task/unsupervised-anomaly-detection-with-specified-4","datasets_with_task":"/datasets/task/unsupervised-anomaly-detection-with-specified-4"},{"name":"Unsupervised Anomaly Detection with Specified Settings -- 1% anomaly","url":"/task/unsupervised-anomaly-detection-with-specified-5","datasets_with_task":"/datasets/task/unsupervised-anomaly-detection-with-specified-5"},{"name":"Unsupervised Anomaly Detection with Specified Settings -- 0.1% anomaly","url":"/task/unsupervised-anomaly-detection-with-specified-6","datasets_with_task":"/datasets/task/unsupervised-anomaly-detection-with-specified-6"},{"name":"Unsupervised Anomaly Detection with Specified Settings -- 10% anomaly","url":"/task/unsupervised-anomaly-detection-with-specified-7","datasets_with_task":"/datasets/task/unsupervised-anomaly-detection-with-specified-7"}],"languages":[],"variants":["cats_vs_dogs"],"data_loaders":[{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/microsoft/cats_vs_dogs","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/huggingface/datasets","url":"https://huggingface.co/datasets/cats_vs_dogs","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/activeloopai/Hub","url":"https://docs.activeloop.ai/datasets/kaggle-cats-and-dogs-dataset","frameworks":["tf","pytorch"]},{"repo":"https://github.com/tensorflow/datasets","url":"https://www.tensorflow.org/datasets/catalog/cats_vs_dogs","frameworks":["tf","pytorch","jax"]},{"repo":"https://github.com/Graviti-AI/datasets","url":"https://gas.graviti.com/dataset/graviti/DogsVsCats","frameworks":["tf","pytorch"]}],"num_papers_in_archive":13,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/unsupervised-anomaly-detection-with-specified-12","task":"Unsupervised Anomaly Detection with Specified Settings -- 0.1% anomaly","dataset_variant":"Cats and Dogs","rows":6,"metrics":["AUC-ROC"],"first_row_in_archive_order":{"model":"RSRAE","paper":"/paper/robust-subspace-recovery-layer-for","metrics":{"AUC-ROC":"0.982"},"code_links":[{"title":"dmzou/RSRAE","url":"https://github.com/dmzou/RSRAE"},{"title":"marrrcin/rsrlayer-pytorch","url":"https://github.com/marrrcin/rsrlayer-pytorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/unsupervised-anomaly-detection-with-specified-24","task":"Unsupervised Anomaly Detection with Specified Settings -- 20% anomaly","dataset_variant":"Cats and Dogs","rows":6,"metrics":["AUC-ROC"],"first_row_in_archive_order":{"model":"Shell-Renormalized","paper":"/paper/shell-theory-a-statistical-model-of-reality","metrics":{"AUC-ROC":"0.953"},"code_links":[{"title":"wen-yan-lin/shell-theory","url":"https://github.com/wen-yan-lin/shell-theory"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/unsupervised-anomaly-detection-with-specified-26","task":"Unsupervised Anomaly Detection with Specified Settings -- 10% anomaly","dataset_variant":"Cats and Dogs","rows":6,"metrics":["AUC-ROC"],"first_row_in_archive_order":{"model":"Shell-Renormalized","paper":"/paper/shell-theory-a-statistical-model-of-reality","metrics":{"AUC-ROC":"0.996"},"code_links":[{"title":"wen-yan-lin/shell-theory","url":"https://github.com/wen-yan-lin/shell-theory"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/unsupervised-anomaly-detection-with-specified-19","task":"Unsupervised Anomaly Detection with Specified Settings -- 1% anomaly","dataset_variant":"Cats and Dogs","rows":5,"metrics":["AUC-ROC"],"first_row_in_archive_order":{"model":"RSRAE","paper":"/paper/robust-subspace-recovery-layer-for","metrics":{"AUC-ROC":"0.981"},"code_links":[{"title":"dmzou/RSRAE","url":"https://github.com/dmzou/RSRAE"},{"title":"marrrcin/rsrlayer-pytorch","url":"https://github.com/marrrcin/rsrlayer-pytorch"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/image-classification-on-cats-vs-dogs-1","task":"Image Classification","dataset_variant":"cats_vs_dogs","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"µ2Net+ (ViT-L/16)","paper":"/paper/a-continual-development-methodology-for-large","metrics":{"Accuracy":"99.83"},"code_links":[{"title":"google-research/google-research","url":"https://github.com/google-research/google-research/tree/master/muNet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/locally-varying-distance-transform-for","title":"Locally varying distance transform for unsupervised visual anomaly detection","date":"2022-10-23","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/a-continual-development-methodology-for-large","title":"A Continual Development Methodology for Large-scale Multitask Dynamic ML Systems","date":"2022-09-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/shell-theory-a-statistical-model-of-reality","title":"Shell Theory: A Statistical Model of Reality","date":"2021-05-28","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/deep-unsupervised-anomaly-detection","title":"Deep unsupervised anomaly detection","date":"2021-01-05","rows_on_this_dataset":4,"code_links":0,"syntology":null},{"paper":"/paper/robust-subspace-recovery-layer-for","title":"Robust Subspace Recovery Layer for Unsupervised Anomaly Detection","date":"2019-03-30","rows_on_this_dataset":4,"code_links":2,"syntology":null},{"paper":"/paper/deep-autoencoding-gaussian-mixture-model-for","title":"Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection","date":"2018-01-01","rows_on_this_dataset":4,"code_links":2,"syntology":null},{"paper":"/paper/isolation-forest","title":"Isolation forest","date":"2008-12-15","rows_on_this_dataset":4,"code_links":0,"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; 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