{"url":"/dataset/uw-iom","name":"UW IOM","full_name":"University of Washington Indoor Object Manipulation","description_markdown":"Comprises twenty individuals picking up and placing objects of varying weights to and from cabinet and table locations at various heights.\r\n\r\nSource: [Toward Ergonomic Risk Prediction via Segmentation of Indoor Object Manipulation Actions Using Spatiotemporal Convolutional Networks](/paper/predicting-ergonomic-risks-during-indoor)","description_withheld":null,"homepage":"https://data.mendeley.com/datasets/xwzzkxtf9s/3","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/predicting-ergonomic-risks-during-indoor","title":"Toward Ergonomic Risk Prediction via Segmentation of Indoor Object Manipulation Actions Using Spatiotemporal Convolutional Networks","first_author":"Behnoosh Parsa","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Action Segmentation","url":"/task/action-segmentation","datasets_with_task":"/datasets/task/action-segmentation"}],"languages":[],"variants":["UW IOM"],"data_loaders":[],"num_papers_in_archive":1,"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."}