{"url":"/dataset/mp-3dhp-multi-person-3d-human-pose-dataset","name":"MP-3DHP: Multi-Person 3D Human Pose Dataset","full_name":null,"description_markdown":"Multi-Person 3D HumanPose Dataset (MP-3DHP) is a depth sensor-based dataset, which was constructed to facilitate the development of multi-person 3D pose estimation methods targeting real-world challenges. The dataset includes 177k training data and 33k validation data where both the 3D human poses and body segments are avaliable. The dataset also include 9k clean background data and 4k testing data including multi-person 3D poses.","description_withheld":null,"homepage":"https://github.com/oppo-us-research/PoP-Net","introduced_date":"2020-12-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/pop-net-pose-over-parts-network-for-multi","title":"PoP-Net: Pose over Parts Network for Multi-Person 3D Pose Estimation from a Depth Image","first_author":"Yuliang Guo","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["MP-3DHP: Multi-Person 3D Human Pose Dataset"],"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":"2026-09-25T09:33:49+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."}