{"url":"/dataset/ut-zappos50k","name":"UT Zappos50K","full_name":null,"description_markdown":"**UT Zappos50K** is a large shoe dataset consisting of 50,025 catalog images collected from Zappos.com. The images are divided into 4 major categories — shoes, sandals, slippers, and boots — followed by functional types and individual brands. The shoes are centered on a white background and pictured in the same orientation for convenient analysis.\r\n\r\nSource: [UT Zappos50K](http://vision.cs.utexas.edu/projects/finegrained/utzap50k/)","description_withheld":null,"homepage":"http://vision.cs.utexas.edu/projects/finegrained/utzap50k/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/fine-grained-visual-comparisons-with-local","title":"Fine-Grained Visual Comparisons with Local Learning","first_author":"Aron Yu","url":null},"license":{"name":"Custom (academic, non-commercial)","url":"http://vision.cs.utexas.edu/projects/finegrained/utzap50k/"},"modalities":[],"tasks":[{"name":"Image Generation","url":"/task/image-generation","datasets_with_task":"/datasets/task/image-generation"},{"name":"Few-Shot Image Classification","url":"/task/few-shot-image-classification","datasets_with_task":"/datasets/task/few-shot-image-classification"},{"name":"Image-to-Image Translation","url":"/task/image-to-image-translation","datasets_with_task":"/datasets/task/image-to-image-translation"},{"name":"Image Captioning","url":"/task/image-captioning","datasets_with_task":"/datasets/task/image-captioning"},{"name":"Compositional Zero-Shot Learning","url":"/task/compositional-zero-shot-learning","datasets_with_task":"/datasets/task/compositional-zero-shot-learning"}],"languages":[],"variants":["UT Zappos50K"],"data_loaders":[{"repo":"https://github.com/activeloopai/Hub","url":"https://docs.activeloop.ai/datasets/utzappos50k-dataset","frameworks":["tf","pytorch"]}],"num_papers_in_archive":32,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/compositional-zero-shot-learning-on-ut","task":"Compositional Zero-Shot Learning","dataset_variant":"UT Zappos50K","rows":1,"metrics":["AUC","Attribute accuracy","Object accuracy","Seen accuracy","Unseen accuracy","best HM"],"first_row_in_archive_order":{"model":"CANet","paper":"/paper/learning-conditional-attributes-for-1","metrics":{"AUC":"33.1","Attribute accuracy":"48.4","Object accuracy":"72.6","Seen accuracy":"61","Unseen accuracy":"66.3","best HM":"47.3"},"code_links":[{"title":"wqshmzh/canet-czsl","url":"https://github.com/wqshmzh/canet-czsl"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/few-shot-image-classification-on-ut-zappos50k","task":"Few-Shot Image Classification","dataset_variant":"UT Zappos50K","rows":1,"metrics":["Top 1 Accuracy"],"first_row_in_archive_order":{"model":"MScon","paper":"/paper/multi-similarity-contrastive-learning","metrics":{"Top 1 Accuracy":"97.17"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/multi-similarity-contrastive-learning","title":"Multi-Similarity Contrastive Learning","date":"2023-07-06","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/learning-conditional-attributes-for-1","title":"Learning Conditional Attributes for Compositional Zero-Shot Learning","date":"2023-05-29","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":9,"samples_ran":6,"samples_unverified":3,"pointer_only_for_licence":9,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":1,"samples_harvested":9,"samples_ran":6,"samples_unverified":3,"pointer_only_for_licence":9,"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."}