{"url":"/dataset/dyml-product","name":"DyML-Product","full_name":"Dynamic Metric Learning Product","description_markdown":"DyML-Product is derived from iMaterialist-2019, a hierarchical online product dataset. The original iMaterialist-2019 offers up to 4 levels of hierarchical annotations. We remove the coarsest level and maintain 3 levels for DyML-Product.\r\n\r\nhttps://github.com/MalongTech/imaterialist-product-2019","description_withheld":null,"homepage":"https://github.com/SupetZYK/DynamicMetricLearning","introduced_date":"2021-03-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/dynamic-metric-learning-towards-a-scalable","title":"Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales","first_author":"Yifan Sun","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Retrieval","url":"/task/image-retrieval","datasets_with_task":"/datasets/task/image-retrieval"},{"name":"Metric Learning","url":"/task/metric-learning","datasets_with_task":"/datasets/task/metric-learning"}],"languages":[],"variants":["DyML-Product"],"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/metric-learning-on-dyml-product","task":"Metric Learning","dataset_variant":"DyML-Product","rows":2,"metrics":["Average-mAP"],"first_row_in_archive_order":{"model":"HAPPIER","paper":"/paper/hierarchical-average-precision-training-for","metrics":{"Average-mAP":"38.0"},"code_links":[{"title":"elias-ramzi/happier","url":"https://github.com/elias-ramzi/happier"},{"title":"elias-ramzi/suprank","url":"https://github.com/elias-ramzi/suprank"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/hierarchical-average-precision-training-for","title":"Hierarchical Average Precision Training for Pertinent Image Retrieval","date":"2022-07-05","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":9,"samples_ran":6,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/dynamic-metric-learning-towards-a-scalable","title":"Dynamic Metric Learning: Towards a Scalable Metric Space to Accommodate Multiple Semantic Scales","date":"2021-03-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":1,"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":10,"samples_ran":6,"samples_unverified":4,"pointer_only_for_licence":1,"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."}