{"url":"/dataset/ntu-rgb-d-2d","name":"NTU RGB+D 2D","full_name":null,"description_markdown":"**NTU RGB+D 2D** is a curated version of [NTU RGB+D](https://paperswithcode.com/dataset/ntu-rgb-d) often used for skeleton-based action prediction and synthesis. It contains less number of actions.","description_withheld":null,"homepage":"https://rose1.ntu.edu.sg/dataset/actionRecognition/","introduced_date":"2016-04-11","introduced_date_note":null,"introduced_by":{"paper":"/paper/ntu-rgbd-a-large-scale-dataset-for-3d-human","title":"NTU RGB+D: A Large Scale Dataset for 3D Human Activity Analysis","first_author":"Amir Shahroudy","url":null},"license":{"name":"Custom (research-only, non-commercial, attribution)","url":"http://rose1.ntu.edu.sg/Datasets/requesterAdd.asp?DS=3"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"}],"tasks":[{"name":"Human action generation","url":"/task/human-action-generation","datasets_with_task":"/datasets/task/human-action-generation"},{"name":"motion prediction","url":"/task/motion-prediction","datasets_with_task":"/datasets/task/motion-prediction"}],"languages":[],"variants":["NTU RGB+D 2D"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/human-action-generation-on-ntu-rgb-d-2d","task":"Human action generation","dataset_variant":"NTU RGB+D 2D","rows":5,"metrics":["MMDa (CS)","MMDs (CS)","MMDa (CV)","MMDs (CV)"],"first_row_in_archive_order":{"model":"Kinetic-GAN","paper":"/paper/generative-adversarial-graph-convolutional","metrics":{"MMDa (CS)":"0.256","MMDa (CV)":"0.295","MMDs (CS)":"0.273","MMDs (CV)":"0.310"},"code_links":[{"title":"degardinbruno/kinetic-gan","url":"https://github.com/degardinbruno/kinetic-gan"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/generative-adversarial-graph-convolutional","title":"Generative Adversarial Graph Convolutional Networks for Human Action Synthesis","date":"2021-10-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/structure-aware-human-action-generation","title":"Structure-Aware Human-Action Generation","date":"2020-07-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-diverse-stochastic-human-action","title":"Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions","date":"2019-12-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":1,"samples_ran":0,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/deep-video-generation-prediction-and","title":"Deep Video Generation, Prediction and Completion of Human Action Sequences","date":"2017-11-23","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/conditional-generative-adversarial-nets","title":"Conditional Generative Adversarial Nets","date":"2014-11-06","rows_on_this_dataset":1,"code_links":62,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":40,"samples_ran":6,"samples_unverified":34,"pointer_only_for_licence":6,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":41,"samples_ran":6,"samples_unverified":35,"pointer_only_for_licence":6,"papers_with_no_sample_that_ran":1,"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."}