{"url":"/dataset/hrsc2016","name":"HRSC2016","full_name":"High resolution ship collections 2016","description_markdown":"High-resolution ship collections 2016 (HRSC2016) is a data set used for scientific research. Currently, all of the images in HRSC2016 were collected from Google Earth.","description_withheld":null,"homepage":"https://www.kaggle.com/guofeng/hrsc2016","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection In Aerial Images","url":"/task/object-detection-in-aerial-images","datasets_with_task":"/datasets/task/object-detection-in-aerial-images"},{"name":"One-stage Anchor-free Oriented Object Detection","url":"/task/one-stage-anchor-free-oriented-object-1","datasets_with_task":"/datasets/task/one-stage-anchor-free-oriented-object-1"}],"languages":[{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":[],"data_loaders":[],"num_papers_in_archive":12,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-in-aerial-images-on-hrsc2016","task":"Object Detection In Aerial Images","dataset_variant":"HRSC2016","rows":9,"metrics":["mAP-07","mAP-12"],"first_row_in_archive_order":{"model":"CDLA-HOP","paper":"/paper/category-aware-dynamic-label-assignment-with","metrics":{"mAP-07":"90.89","mAP-12":"98.77"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/strip-r-cnn-large-strip-convolution-for","title":"Strip R-CNN: Large Strip Convolution for Remote Sensing Object Detection","date":"2025-01-07","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/category-aware-dynamic-label-assignment-with","title":"Category-Aware Dynamic Label Assignment with High-Quality Oriented Proposal","date":"2024-07-03","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/spatial-transform-decoupling-for-oriented","title":"Spatial Transform Decoupling for Oriented Object Detection","date":"2023-08-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/large-selective-kernel-network-for-remote","title":"Large Selective Kernel Network for Remote Sensing Object Detection","date":"2023-03-16","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/rtmdet-an-empirical-study-of-designing-real","title":"RTMDet: An Empirical Study of Designing Real-Time Object Detectors","date":"2022-12-14","rows_on_this_dataset":1,"code_links":14,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":20,"samples_ran":3,"samples_unverified":17,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/an-empirical-study-of-remote-sensing","title":"An Empirical Study of Remote Sensing Pretraining","date":"2022-04-06","rows_on_this_dataset":4,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":20,"samples_ran":3,"samples_unverified":17,"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."}