{"url":"/dataset/texbig","name":"TexBiG","full_name":"Text-Bild-Gefüge","description_markdown":"TexBiG (from the German Text-Bild-Gefüge, meaning Text-Image-Structure) is a document layout analysis dataset for historical documents in the late 19th and early 20th century. The dataset provides instance segmentation (bounding boxes and polygons/masks) annotations for 19 different classes with more then 52.000 instances. \r\n\r\nThe added test images can be used to make submission on the leaderboard on EvalAI: https://eval.ai/web/challenges/challenge-page/2078/overview\r\n\r\nDataset link: https://doi.org/10.5281/zenodo.8347059\r\n\r\n\r\nDataset (only train): https://www.kaggle.com/datasets/davidtschirschwitz/texbig-v2-0-train-val\r\n\r\nDataset (only test image): https://www.kaggle.com/datasets/davidtschirschwitz/texbig-v2-0-test\r\n\r\n\r\nPlease use TexBiG 2023 (which is v2.0 of the dataset) for testing model performance. The test dataset from the 2022 version (v1.0) are included as training data in v2.0\r\n\r\nEach image of the dataset was annotated at least by two different annotators.","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.8347059","introduced_date":"2022-09-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-dataset-for-analysing-complex-document","title":"A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s Alpha","first_author":"David Tschirschwitz","url":null},"license":{"name":"Creative Commons Attribution 4.0 International","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Instance Segmentation","url":"/task/instance-segmentation","datasets_with_task":"/datasets/task/instance-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"},{"name":"German","url":"/datasets/language/german"}],"variants":["TexBiG","TexBiG 2023 test","TexBiG 2022","TexBiG 2022 test"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/instance-segmentation-on-texbig-2022-test","task":"Instance Segmentation","dataset_variant":"TexBiG 2022 test","rows":1,"metrics":["mAP@0.5:0.95:0.05"],"first_row_in_archive_order":{"model":"VSR (Vison, Semantics and Relation Model)","paper":"/paper/a-dataset-for-analysing-complex-document","metrics":{"mAP@0.5:0.95:0.05":"65.8"},"code_links":[{"title":"Madave94/kalphacv","url":"https://github.com/Madave94/kalphacv"},{"title":"Madave94/VSR-TexBiG-Dataset","url":"https://github.com/Madave94/VSR-TexBiG-Dataset"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/instance-segmentation-on-texbig-2023-test","task":"Instance Segmentation","dataset_variant":"TexBiG 2023 test","rows":1,"metrics":["mAP@0.5:0.95:0.05"],"first_row_in_archive_order":{"model":"DetectoRS + LAEM","paper":"/paper/drawing-the-same-bounding-box-twice-coping","metrics":{"mAP@0.5:0.95:0.05":"44.06"},"code_links":[{"title":"madave94/gtiod","url":"https://github.com/madave94/gtiod"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-detection-on-texbig-2022-test","task":"Object Detection","dataset_variant":"TexBiG 2022 test","rows":1,"metrics":["mAP@0.5:0.95:0.05"],"first_row_in_archive_order":{"model":"VSR (Vison, Semantics and Relation Model)","paper":"/paper/a-dataset-for-analysing-complex-document","metrics":{"mAP@0.5:0.95:0.05":"75.9"},"code_links":[{"title":"Madave94/kalphacv","url":"https://github.com/Madave94/kalphacv"},{"title":"Madave94/VSR-TexBiG-Dataset","url":"https://github.com/Madave94/VSR-TexBiG-Dataset"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-detection-on-texbig-2023-test","task":"Object Detection","dataset_variant":"TexBiG 2023 test","rows":1,"metrics":["mAP@0.5:0.95:0.05"],"first_row_in_archive_order":{"model":"DetectoRS + LAEM","paper":"/paper/drawing-the-same-bounding-box-twice-coping","metrics":{"mAP@0.5:0.95:0.05":"49.89"},"code_links":[{"title":"madave94/gtiod","url":"https://github.com/madave94/gtiod"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/drawing-the-same-bounding-box-twice-coping","title":"Drawing the Same Bounding Box Twice? Coping Noisy Annotations in Object Detection with Repeated Labels","date":"2023-09-18","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/a-dataset-for-analysing-complex-document","title":"A Dataset for Analysing Complex Document Layouts in the Digital Humanities and Its Evaluation with Krippendorff’s Alpha","date":"2022-09-20","rows_on_this_dataset":2,"code_links":2,"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."}