{"url":"/dataset/flag3d","name":"FLAG3D","full_name":null,"description_markdown":"**FLAG3D** is a large-scale 3D fitness activity dataset with language instruction containing 180K sequences of 60 categories. FLAG3D features the following three aspects: 1) accurate and dense 3D human pose captured from advanced MoCap system to handle the complex activity and large movement, 2) detailed and professional language instruction to describe how to perform a specific activity, 3) versatile video resources from a high-tech MoCap system, rendering software, and cost-effective smartphones in natural environments.\r\n\r\nSource: [FLAG3D: A 3D Fitness Activity Dataset with Language Instruction](https://arxiv.org/pdf/2212.04638v1.pdf)\r\n\r\nImage Source: [https://arxiv.org/pdf/2212.04638v1.pdf](https://arxiv.org/pdf/2212.04638v1.pdf)","description_withheld":null,"homepage":"https://andytang15.github.io/FLAG3D","introduced_date":"2022-12-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/flag3d-a-3d-fitness-activity-dataset-with","title":"FLAG3D: A 3D Fitness Activity Dataset with Language Instruction","first_author":"Yansong Tang","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"},{"name":"3D","url":"/datasets/modality/3d"}],"tasks":[{"name":"3D Action Recognition","url":"/task/3d-human-action-recognition","datasets_with_task":"/datasets/task/3d-human-action-recognition"},{"name":"Human Activity Recognition","url":"/task/human-activity-recognition","datasets_with_task":"/datasets/task/human-activity-recognition"},{"name":"Human action generation","url":"/task/human-action-generation","datasets_with_task":"/datasets/task/human-action-generation"},{"name":"Human Mesh Recovery","url":"/task/human-mesh-recovery","datasets_with_task":"/datasets/task/human-mesh-recovery"}],"languages":[],"variants":["FLAG3D"],"data_loaders":[],"num_papers_in_archive":4,"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."}