{"url":"/dataset/wildreceipt","name":"WildReceipt","full_name":null,"description_markdown":"WildReceipt is a collection  of receipts. \r\nIt contains, for each photo, of a list of OCRs - with bounding box, text, and class. \r\n\r\nIt contains 1765 photos, with 25 classes, and 50000 text boxes. \r\nThe goal is to benchmark \"key information extraction\" - extracting key information from documents. There are two different modalities - text and visual features - which is an interesting problem. \r\nPotential uses - extracting information from documents.\r\n\r\n*The dataset is pending release.*","description_withheld":null,"homepage":"","introduced_date":"2021-03-26","introduced_date_note":null,"introduced_by":{"paper":"/paper/spatial-dual-modality-graph-reasoning-for-key","title":"Spatial Dual-Modality Graph Reasoning for Key Information Extraction","first_author":"Hongbin Sun","url":null},"license":{"name":"None","url":"https://download.openmmlab.com/mmocr/data/wildreceipt.tar"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["WildReceipt"],"data_loaders":[],"num_papers_in_archive":8,"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."}