{"url":"/dataset/mall","name":"Mall","full_name":"Mall Dataset","description_markdown":"The **Mall** is a dataset for crowd counting and profiling research. Its images are collected from publicly accessible webcam. It mainly includes 2,000 video frames, and the head position of every pedestrian in all frames is annotated. A total of more than 60,000 pedestrians are annotated in this dataset.\r\n\r\nSource: [Drone Based RGBT Vehicle Detection and Counting: A Challenge](https://arxiv.org/abs/2003.02437)\r\nImage Source: [http://www.bmva.org/bmvc/2012/BMVC/paper021/paper021.pdf](http://www.bmva.org/bmvc/2012/BMVC/paper021/paper021.pdf)","description_withheld":null,"homepage":"http://vision.cs.tut.fi/personal/kechen/codedata.html","introduced_date":"2012-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"Feature Mining for Localised Crowd Counting","first_author":null,"url":"https://doi.org/10.5244/C.26.21"},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Object Localization","url":"/task/object-localization","datasets_with_task":"/datasets/task/object-localization"}],"languages":[],"variants":["Mall"],"data_loaders":[],"num_papers_in_archive":64,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/object-localization-on-mall","task":"Object Localization","dataset_variant":"Mall","rows":1,"metrics":["Precision"],"first_row_in_archive_order":{"model":"Hausdorff Loss","paper":"/paper/weighted-hausdorff-distance-a-loss-function","metrics":{"Precision":"88.1"},"code_links":[{"title":"javiribera/locating-objects-without-bboxes","url":"https://github.com/javiribera/locating-objects-without-bboxes"},{"title":"HaipengXiong/weighted-hausdorff-loss","url":"https://github.com/HaipengXiong/weighted-hausdorff-loss"},{"title":"Nacriema/Loss-Functions-For-Semantic-Segmentation","url":"https://github.com/Nacriema/Loss-Functions-For-Semantic-Segmentation"},{"title":"danielenricocahall/Keras-Weighted-Hausdorff-Distance-Loss","url":"https://github.com/danielenricocahall/Keras-Weighted-Hausdorff-Distance-Loss"},{"title":"N0vel/weighted-hausdorff-distance-tensorflow-keras-loss","url":"https://github.com/N0vel/weighted-hausdorff-distance-tensorflow-keras-loss"},{"title":"vnbot2/object-locator","url":"https://github.com/vnbot2/object-locator"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/weighted-hausdorff-distance-a-loss-function","title":"Locating Objects Without Bounding Boxes","date":"2018-06-20","rows_on_this_dataset":1,"code_links":6,"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."}