{"url":"/dataset/egoism-hoi","name":"EgoISM-HOI","full_name":null,"description_markdown":"EgoISM-HOI is a new multimodal dataset composed of synthetic and real images of egocentric human-objects interactions in an industrial environment with rich annotations of hands and objects. EgoISM-HOI contains a total of 39,304 RGB images, 23,356 depth maps and instance segmentation masks, 59,860 hand annotations, 237,985 object instances across 19 object categories and 35,416 egocentric human-object interactions.","description_withheld":null,"homepage":"https://iplab.dmi.unict.it/egoism-hoi/","introduced_date":"2023-06-21","introduced_date_note":null,"introduced_by":{"paper":"/paper/exploiting-multimodal-synthetic-data-for","title":"Exploiting Multimodal Synthetic Data for Egocentric Human-Object Interaction Detection in an Industrial Scenario","first_author":"Rosario Leonardi","url":null},"license":null,"modalities":[],"tasks":[{"name":"Human-Object Interaction Detection","url":"/task/human-object-interaction-detection","datasets_with_task":"/datasets/task/human-object-interaction-detection"}],"languages":[],"variants":["EgoISM-HOI"],"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."}