{"url":"/dataset/citystreet","name":"CityStreet","full_name":null,"description_markdown":"Datasets for multi-view crowd counting in wide-area scenes. Includes our CityStreet dataset, as well as the counting and metadata for multi-view counting on PETS2009 and DukeMTMC.\r\nCityStreet is a real-world city scene dataset collected around the intersection of a crowded street. The scene size of the dataset is around 58m×72m. The ground plane map resolution is 320×384.","description_withheld":null,"homepage":"http://visal.cs.cityu.edu.hk/downloads/citystreetdata/","introduced_date":"2019-06-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/wide-area-crowd-counting-via-ground-plane","title":"Wide-Area Crowd Counting via Ground-Plane Density Maps and Multi-View Fusion CNNs","first_author":"Qi Zhang","url":null},"license":null,"modalities":[],"tasks":[{"name":"Crowd Counting","url":"/task/crowd-counting","datasets_with_task":"/datasets/task/crowd-counting"},{"name":"Multiview Detection","url":"/task/multiview-detection","datasets_with_task":"/datasets/task/multiview-detection"}],"languages":[],"variants":["CityStreet"],"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/multiview-detection-on-citystreet","task":"Multiview Detection","dataset_variant":"CityStreet","rows":5,"metrics":["MODA (2m)","MODP (2m)","Precision (2m)","Recall (2m)","F1_score (2m)"],"first_row_in_archive_order":{"model":"3DROM","paper":"/paper/3d-random-occlusion-and-multi-layer","metrics":{"F1_score (2m)":"79.2","MODA (2m)":"60.0","MODP (2m)":"70.1","Precision (2m)":"82.5","Recall (2m)":"76.2"},"code_links":[{"title":"xjtlu-cvlab/3drom","url":"https://github.com/xjtlu-cvlab/3drom"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/multi-view-people-detection-in-large-scenes","title":"Multi-View People Detection in Large Scenes via Supervised View-Wise Contribution Weighting","date":"2024-05-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/3d-random-occlusion-and-multi-layer","title":"3D Random Occlusion and Multi-Layer Projection for Deep Multi-Camera Pedestrian Localization","date":"2022-07-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":8,"samples_ran":2,"samples_unverified":6,"pointer_only_for_licence":8,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multiview-detection-with-shadow-transformer","title":"Multiview Detection with Shadow Transformer (and View-Coherent Data Augmentation)","date":"2021-08-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/stacked-homography-transformations-for-multi","title":"Stacked Homography Transformations for Multi-View Pedestrian Detection","date":"2021-01-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/multiview-detection-with-feature-perspective","title":"Multiview Detection with Feature Perspective Transformation","date":"2020-07-14","rows_on_this_dataset":1,"code_links":3,"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":9,"samples_ran":2,"samples_unverified":7,"pointer_only_for_licence":9,"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."}