{"url":"/dataset/u-diads-bib","name":"U-DIADS-Bib","full_name":null,"description_markdown":"U-DIADS-Bib is a proprietary dataset developed through the collaboration of computer scientists and humanities at the University of Udine. It is composed of 200 images, 50 for each of the 4 different manuscripts that characterize it. These handwritten books were selected in collaboration with humanist partners considering both the complexity of their layout and the presence of significant and semantically distinguishable elements. In particular, the images of the four manuscripts were collected from the digital library Gallica. All manuscripts are Latin and Syriac Bibles published between the 6th and 12th centuries A.D.","description_withheld":null,"homepage":"https://ai4ch.uniud.it/udiadsbib/","introduced_date":"2024-01-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/u-diads-bib-a-full-and-few-shot-pixel-precise","title":"U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts","first_author":"Silvia Zottin","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Document Layout Analysis","url":"/task/document-layout-analysis","datasets_with_task":"/datasets/task/document-layout-analysis"},{"name":"Handwritten Document Recognition","url":"/task/handwritten-document-recognition","datasets_with_task":"/datasets/task/handwritten-document-recognition"},{"name":"document understanding","url":"/task/document-understanding","datasets_with_task":"/datasets/task/document-understanding"}],"languages":[],"variants":["U-DIADS-Bib"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/document-layout-analysis-on-u-diads-bib","task":"Document Layout Analysis","dataset_variant":"U-DIADS-Bib","rows":5,"metrics":["Class Average IoU","Class Average IoU (Few-shot setting)"],"first_row_in_archive_order":{"model":"CV-Group","paper":"/paper/icdar-2024-competition-on-few-shot-and-many","metrics":{"Class Average IoU":"83.40","Class Average IoU (Few-shot setting)":"78.40"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/icdar-2024-competition-on-few-shot-and-many","title":"ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)","date":"2024-09-11","rows_on_this_dataset":4,"code_links":0,"syntology":null},{"paper":"/paper/u-diads-bib-a-full-and-few-shot-pixel-precise","title":"U-DIADS-Bib: a full and few-shot pixel-precise dataset for document layout analysis of ancient manuscripts","date":"2024-01-16","rows_on_this_dataset":1,"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; 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."}