{"url":"/dataset/openimages-v6","name":"OpenImages-v6","full_name":null,"description_markdown":"OpenImages V6 is a large-scale dataset ,\r\nconsists of 9 million training images, 41,620 validation\r\nsamples, and 125,456 test samples. It is a partially annotated dataset, with 9,600 trainable classes","description_withheld":null,"homepage":"https://storage.googleapis.com/openimages/web/index.html","introduced_date":"2018-11-02","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-open-images-dataset-v4-unified-image","title":"The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale","first_author":"Alina Kuznetsova","url":null},"license":{"name":"Apache License 2.0","url":"https://github.com/openimages/dataset/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Multi-Label Classification","url":"/task/multi-label-classification","datasets_with_task":"/datasets/task/multi-label-classification"},{"name":"Unsupervised Object Detection","url":"/task/unsupervised-object-detection","datasets_with_task":"/datasets/task/unsupervised-object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["OpenImages-v6"],"data_loaders":[{"repo":"https://github.com/voxel51/fiftyone","url":"https://docs.voxel51.com/user_guide/dataset_zoo/datasets.html#open-images-v6","frameworks":["tf","pytorch"]}],"num_papers_in_archive":23,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-label-classification-on-openimages-v6","task":"Multi-Label Classification","dataset_variant":"OpenImages-v6","rows":4,"metrics":["mAP"],"first_row_in_archive_order":{"model":"TResNet-L","paper":"/paper/multi-label-classification-with-partial","metrics":{"mAP":"87.34"},"code_links":[{"title":"alibaba-miil/partiallabelingcsl","url":"https://github.com/alibaba-miil/partiallabelingcsl"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-detection-on-openimages-v6","task":"Object Detection","dataset_variant":"OpenImages-v6","rows":2,"metrics":["box AP"],"first_row_in_archive_order":{"model":"ScaleDet","paper":"/paper/scaledet-a-scalable-multi-dataset-object-1","metrics":{"box AP":"76.2"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/scaledet-a-scalable-multi-dataset-object-1","title":"ScaleDet: A Scalable Multi-Dataset Object Detector","date":"2023-06-08","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/internimage-exploring-large-scale-vision","title":"InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions","date":"2022-11-10","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":2,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/ml-decoder-scalable-and-versatile","title":"ML-Decoder: Scalable and Versatile Classification Head","date":"2021-11-25","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":5,"samples_ran":2,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multi-label-classification-with-partial","title":"Multi-label Classification with Partial Annotations using Class-aware Selective Loss","date":"2021-10-21","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/asymmetric-loss-for-multi-label","title":"Asymmetric Loss For Multi-Label Classification","date":"2020-09-29","rows_on_this_dataset":1,"code_links":5,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":4,"samples_unverified":8,"pointer_only_for_licence":7,"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":3,"samples_harvested":21,"samples_ran":8,"samples_unverified":13,"pointer_only_for_licence":7,"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."}