{"url":"/dataset/sku110k","name":"SKU110K","full_name":"SKU110K","description_markdown":"The Sku110k dataset provides 11,762 images with more than 1.7 million annotated bounding boxes captured in densely packed scenarios, including 8,233 images for training, 588 images for validation, and 2,941 images for testing. There are around 1,733,678 instances in total. The images are collected from thousands of supermarket stores and are of various scales, viewing angles, lighting conditions, and noise levels. All the images are resized into a resolution of one megapixel. Most of the instances in the dataset are tightly packed and typically of a certain orientation in the rage of [−15∘, 15∘].\n\nSource: [Rethinking Object Detection in Retail Stores](https://arxiv.org/abs/2003.08230)\nImage Source: [https://github.com/eg4000/SKU110K_CVPR19](https://github.com/eg4000/SKU110K_CVPR19)","description_withheld":null,"homepage":"https://github.com/eg4000/SKU110K_CVPR19","introduced_date":"2019-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/precise-detection-in-densely-packed-scenes","title":"Precise Detection in Densely Packed Scenes","first_author":"Eran Goldman","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"One-Shot Object Detection","url":"/task/one-shot-object-detection","datasets_with_task":"/datasets/task/one-shot-object-detection"},{"name":"Dense Object Detection","url":"/task/dense-object-detection","datasets_with_task":"/datasets/task/dense-object-detection"}],"languages":[],"variants":["SKU-110K","SKU110K"],"data_loaders":[{"repo":"https://github.com/eg4000/SKU110K_CVPR19","url":"https://github.com/eg4000/SKU110K_CVPR19","frameworks":["tf"]}],"num_papers_in_archive":22,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/dense-object-detection-on-sku-110k","task":"Dense Object Detection","dataset_variant":"SKU-110K","rows":5,"metrics":["AP","AP75"],"first_row_in_archive_order":{"model":"RetailDet","paper":"/paper/unitail-detecting-reading-and-matching-in","metrics":{"AP":"59.0"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/unitail-detecting-reading-and-matching-in","title":"Unitail: Detecting, Reading, and Matching in Retail Scene","date":"2022-04-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/a-solution-to-product-detection-in-densely","title":"A Solution to Product detection in Densely Packed Scenes","date":"2020-07-23","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/soft-anchor-point-object-detection","title":"Soft Anchor-Point Object Detection","date":"2019-11-27","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/precise-detection-in-densely-packed-scenes","title":"Precise Detection in Densely Packed Scenes","date":"2019-04-01","rows_on_this_dataset":1,"code_links":5,"syntology":null},{"paper":"/paper/focal-loss-for-dense-object-detection","title":"Focal Loss for Dense Object Detection","date":"2017-08-07","rows_on_this_dataset":1,"code_links":234,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":11,"samples_unverified":0,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":17,"samples_ran":11,"samples_unverified":6,"pointer_only_for_licence":6,"papers_with_no_sample_that_ran":1,"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."}