{"url":"/dataset/mogaze","name":"MoGaze","full_name":null,"description_markdown":"**MoGaze** is a dataset of full-body motion for everyday manipulation tasks, which includes 1) long sequences of manipulation tasks, 2) the 3D model of the workspace geometry, and 3) eye-gaze. The motion data was captured using a traditional motion capture system based on reflective markers. The eye-gaze was captured using a wearable pupil-tracking device.\r\n\r\nThe dataset includes 180 min of motion capture data with 1627 pick and place actions being performed.","description_withheld":null,"homepage":"https://humans-to-robots-motion.github.io/mogaze/","introduced_date":"2020-11-23","introduced_date_note":null,"introduced_by":{"paper":"/paper/mogaze-a-dataset-of-full-body-motions-that","title":"MoGaze: A Dataset of Full-Body Motions that Includes Workspace Geometry and Eye-Gaze","first_author":null,"url":null},"license":{"name":"Unknown","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["MoGaze"],"data_loaders":[],"num_papers_in_archive":10,"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."}