{"url":"/dataset/cvcs","name":"CVCS","full_name":"Cross-View Cross-Scene Multi-View Crowd Counting Dataset","description_markdown":"CVCS is a synthetic multi-view people dataset, containing 31 scenes, where 23 are for training and the rest 8 for testing. The scene size varies from about 10m∗20m to 90m∗80m. Each scene contains 100 multi-view frames. The ground plane map resolution is 900×800, where each grid stands for 0.1 meters in the real world. In training, 5 views are randomly selected 5 times in each iteration per scene frame, and the same view number is randomly selected 21 times in evaluation.","description_withheld":null,"homepage":"http://visal.cs.cityu.edu.hk/downloads/citystreetdata/","introduced_date":"2022-05-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/cross-view-cross-scene-multi-view-crowd-1","title":"Cross-View Cross-Scene Multi-View Crowd Counting","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":["CVCS"],"data_loaders":[],"num_papers_in_archive":10,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multiview-detection-on-cvcs","task":"Multiview Detection","dataset_variant":"CVCS","rows":6,"metrics":["MODA (0.5m)","F1_score (0.5m)","MODA (1m)","MODP (1m)","Precision (1m)","Recall (1m)","F1_score (1m)"],"first_row_in_archive_order":{"model":"M-MVOT","paper":"/paper/mahalanobis-distance-based-multi-view-optimal","metrics":{"MODA (0.5m)":"43.5","MODA (1m)":"/"},"code_links":[{"title":"zqyq/Mahalanobis-Distance-based-Multi-view-Optimal-Transport-for-Multi-view-Crowd-Localization","url":"https://github.com/zqyq/Mahalanobis-Distance-based-Multi-view-Optimal-Transport-for-Multi-view-Crowd-Localization"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mahalanobis-distance-based-multi-view-optimal","title":"Mahalanobis Distance-based Multi-view Optimal Transport for Multi-view Crowd Localization","date":"2024-09-03","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"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."}