{"url":"/dataset/obman-ego","name":"ObMan-Ego","full_name":null,"description_markdown":"The ObMan-Ego is a large-scale synthetic hand dataset with egocentric scenes in which the simulated hands are provided by ObMan. The dataset is used for a hand segmentation task and its sim-to-real adaptation benchmark. Training, validation, and testing sets contain 150, 000, 6, 500, and 6, 500 images, respectively.","description_withheld":null,"homepage":"https://tkhkaeio.github.io/projects/21_FgSty-CPL/","introduced_date":"2021-07-06","introduced_date_note":null,"introduced_by":{"paper":"/paper/foreground-aware-stylization-and-consensus","title":"Foreground-Aware Stylization and Consensus Pseudo-Labeling for Domain Adaptation of First-Person Hand Segmentation","first_author":"Takehiko Ohkawa","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Hand Segmentation","url":"/task/hand-segmentation","datasets_with_task":"/datasets/task/hand-segmentation"}],"languages":[],"variants":["ObMan-Ego"],"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."}