{"url":"/dataset/seadronessee","name":"SeaDronesSee","full_name":"SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water","description_markdown":"SeaDronesSee is a large-scale data set aimed at helping develop systems for Search and Rescue (SAR) using Unmanned Aerial Vehicles (UAVs) in maritime scenarios. Building highly complex autonomous UAV systems that aid in SAR missions requires robust computer vision algorithms to detect and track objects or persons of interest. This data set provides three sets of tracks: object detection, single-object tracking and multi-object tracking. Each track consists of its own data set and leaderboard.\r\n\r\nObject Detection: 5,630 train images, 859 validation images, 1,796 testing images\r\n\r\nSingle-Object Tracking: 58 training video clips, 70 validation video clips and 80 testing video clips\r\n\r\nMulti-Object Tracking: 22 video clips with 54,105 frames\r\nAdditionally, we provide multi-spektral footage:\r\n\r\nMulti-Spektral Object Detection: 246 train images, 61 validation images, 125 testing images\r\n\r\nWe will continue to update this data set to make it more versatile and reflect real-world requirements in dynamic situations.","description_withheld":null,"homepage":"https://seadronessee.cs.uni-tuebingen.de/","introduced_date":"2022-01-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/seadronessee-a-maritime-benchmark-for","title":"SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water","first_author":"Leon Amadeus Varga","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Object Tracking","url":"/task/object-tracking","datasets_with_task":"/datasets/task/object-tracking"},{"name":"Multi-Object Tracking","url":"/task/multi-object-tracking","datasets_with_task":"/datasets/task/multi-object-tracking"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["SeaDronesSee"],"data_loaders":[],"num_papers_in_archive":18,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-detection-on-seadronessee","task":"Object Detection","dataset_variant":"SeaDronesSee","rows":10,"metrics":["mAP@0.5","mAP@0.50"],"first_row_in_archive_order":{"model":"Synth Pretrained Faster R-CNN ResNeXt-101-FPN","paper":"/paper/leveraging-synthetic-data-in-object-detection","metrics":{"mAP@0.5":"59.20"},"code_links":[{"title":"Eisbaer8/DeepGTAV","url":"https://github.com/Eisbaer8/DeepGTAV"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-tracking-on-seadronessee","task":"Object Tracking","dataset_variant":"SeaDronesSee","rows":5,"metrics":["Success Rate","Precision Score"],"first_row_in_archive_order":{"model":"DiMP50","paper":"/paper/seadronessee-a-maritime-benchmark-for","metrics":{"Precision Score":"86.84020","Success Rate":"67.33400"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-object-tracking-on-seadronessee","task":"Multi-Object Tracking","dataset_variant":"SeaDronesSee","rows":3,"metrics":["MOTA"],"first_row_in_archive_order":{"model":"Tracktor++","paper":"/paper/seadronessee-a-maritime-benchmark-for","metrics":{"MOTA":"0.7190"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/leveraging-synthetic-data-in-object-detection","title":"Leveraging Synthetic Data in Object Detection on Unmanned Aerial Vehicles","date":"2021-12-22","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/seadronessee-a-maritime-benchmark-for","title":"SeaDronesSee: A Maritime Benchmark for Detecting Humans in Open Water","date":"2021-05-05","rows_on_this_dataset":14,"code_links":0,"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."}