{"url":"/dataset/dip-imu","name":"DIP-IMU","full_name":null,"description_markdown":"Dataset consisting of IMU measurements and corresponding SMPL poses. Participants were wearing 17 IMU sensors and reference SMPL poses were obtained by running the SIP optimization with all 17 sensors.","description_withheld":null,"homepage":"https://dip.is.tue.mpg.de/","introduced_date":"2018-10-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/deep-inertial-poser-learning-to-reconstruct","title":"Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time","first_author":"Yinghao Huang","url":null},"license":{"name":"For non-commercial scientific research purposes","url":"https://dip.is.tue.mpg.de/license.html"},"modalities":[],"tasks":[],"languages":[],"variants":["DIP-IMU"],"data_loaders":[],"num_papers_in_archive":15,"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."}