{"url":"/dataset/soda-d","name":"SODA-D","full_name":null,"description_markdown":"SODA-D is a large-scale dataset tailored for small object detection in driving scenario, which is built on top of MVD dataset and owned data, where the former is a dataset dedicated to pixel-level understanding of street scenes, and the latter is mainly captured by onboard cameras and mobile phones. With 24704 well-chosen and high-quality images of driving scenarios, SODA-D comprises 277596 instances of 9 categories with horizontal bounding boxes.","description_withheld":null,"homepage":"https://shaunyuan22.github.io/SODA/","introduced_date":"2022-07-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/towards-large-scale-small-object-detection","title":"Towards Large-Scale Small Object Detection: Survey and Benchmarks","first_author":"Gong Cheng","url":null},"license":{"name":"CC-BY-SA license agreement","url":"https://creativecommons.org/licenses/by-nc/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Autonomous Driving","url":"/task/autonomous-driving","datasets_with_task":"/datasets/task/autonomous-driving"},{"name":"Small Object Detection","url":"/task/small-object-detection","datasets_with_task":"/datasets/task/small-object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["SODA-D"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/small-object-detection-on-soda-d","task":"Small Object Detection","dataset_variant":"SODA-D","rows":1,"metrics":["mAP@0.5:0.95"],"first_row_in_archive_order":{"model":"CFINet","paper":"/paper/small-object-detection-via-coarse-to-fine","metrics":{"mAP@0.5:0.95":"30.7"},"code_links":[{"title":"shaunyuan22/cfinet","url":"https://github.com/shaunyuan22/cfinet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/small-object-detection-via-coarse-to-fine","title":"Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning","date":"2023-08-18","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":3,"samples_unverified":3,"pointer_only_for_licence":0,"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":1,"samples_harvested":6,"samples_ran":3,"samples_unverified":3,"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."}