{"url":"/dataset/fpds","name":"FPDS","full_name":"Fallen People Data Set","description_markdown":"A benchmark for detecting fallen people lying on the floor. It consists of 6982 images, with a total of 5023 falls and 2275 non falls corresponding to people in conventional situations (standing up, sitting, lying on the sofa or bed, walking, etc). Almost all the images have been captured in indoor environments with very different situations: variation of poses and sizes, occlusions, lighting changes, etc.\r\n\r\nSource: [FPDS](http://agamenon.tsc.uah.es/Investigacion/gram/papers/fall_detection/)","description_withheld":null,"homepage":"http://agamenon.tsc.uah.es/Investigacion/gram/papers/fall_detection/","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/fast-and-robust-detection-of-fallen-people","title":"Fast and Robust Detection of Fallen People from a Mobile Robot","first_author":"Morris Antonello","url":null},"license":null,"modalities":[],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Robot Navigation","url":"/task/robot-navigation","datasets_with_task":"/datasets/task/robot-navigation"}],"languages":[],"variants":["FPDS"],"data_loaders":[{"repo":"https://github.com/VolobuevVV/TestModels","url":"https://github.com/VolobuevVV/TestModels","frameworks":["tf"]}],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}