{"url":"/dataset/unitail","name":"Unitail","full_name":"The United Retail Datasets","description_markdown":"The United Retail Datasets (Unitail) is a large-scale benchmark of basic visual tasks on products that challenges algorithms for detecting, reading, and matching. It offers the Unitial-Det, with 1.8M quadrilateral-shaped instances annotated; and the Unitial-OCR, containing 1454 product categories, 30k text regions, and 21k transcriptions to enable robust reading on products and motivate enhanced product matching.","description_withheld":null,"homepage":"https://unitedretail.github.io/","introduced_date":"2022-04-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/unitail-detecting-reading-and-matching-in","title":"Unitail: Detecting, Reading, and Matching in Retail Scene","first_author":"Fangyi Chen","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["Unitail"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}