{"url":"/dataset/gta-human-ii-dataset","name":"GTA-Human II","full_name":null,"description_markdown":"This is the latest version of our datasets, and is built upon GTA-V for expressive human pose and shape estimation. It features multi-person scenes with SMPL-X annotations. In addition to color image sequences, 3D bounding boxes and cropped point clouds (generated from synthetic depth images) are also provided. Please contact Zhongang Cai (caiz0023@e.ntu.edu.sg) for feedback.","description_withheld":null,"homepage":"https://caizhongang.com/projects/GTA-Human/gta-human_v2.html","introduced_date":"2021-10-14","introduced_date_note":null,"introduced_by":{"paper":"/paper/playing-for-3d-human-recovery","title":"Playing for 3D Human Recovery","first_author":"Zhongang Cai","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["GTA-Human II"],"data_loaders":[],"num_papers_in_archive":2,"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."}