{"url":"/dataset/kolektorsdd","name":"KolektorSDD","full_name":"Kolektor Surface-Defect Dataset","description_markdown":"The dataset is constructed from images of defective production items that were provided and annotated by [Kolektor Group d.o.o.](https://www.kolektordigital.com/en/advanced-visual-tecnologies). The images were captured in a controlled industrial environment in a real-world case.\r\n\r\nThe dataset consists of 399 images at 500 x ~1250 px in size.\r\n\r\nPlease cite our paper published in the Journal of Intelligent Manufacturing when using this dataset:\r\n\r\n```\r\n@article{Tabernik2019JIM,\r\n  author = {Tabernik, Domen and {\\v{S}}ela, Samo and Skvar{\\v{c}}, Jure and \r\n  Sko{\\v{c}}aj, Danijel},\r\n  journal = {Journal of Intelligent Manufacturing},\r\n  title = {{Segmentation-Based Deep-Learning Approach for Surface-Defect Detection}},\r\n  year = {2019},\r\n  month = {May},\r\n  day = {15},\r\n  issn={1572-8145},\r\n  doi={10.1007/s10845-019-01476-x}\r\n}\r\n```","description_withheld":null,"homepage":"https://www.vicos.si/Downloads/KolektorSDD","introduced_date":"2019-03-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/segmentation-based-deep-learning-approach-for","title":"Segmentation-Based Deep-Learning Approach for Surface-Defect Detection","first_author":"Domen Tabernik","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Unsupervised Anomaly Detection","url":"/task/unsupervised-anomaly-detection","datasets_with_task":"/datasets/task/unsupervised-anomaly-detection"},{"name":"Defect Detection","url":"/task/defect-detection","datasets_with_task":"/datasets/task/defect-detection"},{"name":"Weakly Supervised Defect Detection","url":"/task/weakly-supervised-defect-detection","datasets_with_task":"/datasets/task/weakly-supervised-defect-detection"}],"languages":[],"variants":["KolektorSDD"],"data_loaders":[],"num_papers_in_archive":15,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/unsupervised-anomaly-detection-on-kolektorsdd","task":"Unsupervised Anomaly Detection","dataset_variant":"KolektorSDD","rows":1,"metrics":["Segmentation AUROC"],"first_row_in_archive_order":{"model":"Semi-orthogonal","paper":"/paper/semi-orthogonal-embedding-for-efficient","metrics":{"Segmentation AUROC":"96.0"},"code_links":[{"title":"jnhwkim/orthoad","url":"https://github.com/jnhwkim/orthoad"},{"title":"Ultranity/Anomaly.Paddle","url":"https://github.com/Ultranity/Anomaly.Paddle"},{"title":"Pangoraw/SemiOrthogonal","url":"https://github.com/Pangoraw/SemiOrthogonal"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/semi-orthogonal-embedding-for-efficient","title":"Semi-orthogonal Embedding for Efficient Unsupervised Anomaly Segmentation","date":"2021-05-31","rows_on_this_dataset":1,"code_links":3,"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."}