{"url":"/dataset/nuisi-dataset","name":"NuiSI Dataset","full_name":"Nuitrack Skeleton Interaction Dataset","description_markdown":"The NuiSI dataset contains skeleton tracking trajectories of Human Interaction Partners performing a variety of physically interactive behaviors (waving, handshaking, rocket fistbump, parachute fistbump) with each other. This is inspired by the dataset in Bütepage et al. \"Imitating by generating: Deep generative models for imitation of interactive tasks.\" Frontiers in Robotics and AI  (2020) wherein they capture a dataset with rokoko motion capture suits. Instead we track the skeletons of the interaction partner with Intel Realsense cameras using Nuitrack, for a more realistic scenario, with noise coming from the depth sensor, the skeleton tracking and some partial occlusions. This makes it more representative of real world interactions with a Robot equipped with an RGBD camera.\r\nT\r\nThis dataset is used in our papers for training Interaction models for Human-Robot Interaction with a humanoid social robot. If you find the dataset useful in your work, please cite our paper:\r\n\r\nPrasad, V., Heitlinger, L., Koert, D., Stock-Homburg, R., Peters, J., & Chalvatzaki, G. (2023). Learning multimodal latent dynamics for human-robot interaction. arXiv preprint arXiv:2311.16380.\r\n\r\n@article{prasad2023learning,\r\n  title={Learning multimodal latent dynamics for human-robot interaction},\r\n  author={Prasad, Vignesh and Heitlinger, Lea and Koert, Dorothea and Stock-Homburg, Ruth and Peters, Jan and Chalvatzaki, Georgia},\r\n  journal={arXiv preprint arXiv:2311.16380},\r\n  year={2023}\r\n}","description_withheld":null,"homepage":"https://github.com/souljaboy764/nuisi_dataset","introduced_date":"2023-11-27","introduced_date_note":null,"introduced_by":{"paper":"/paper/moveint-mixture-of-variational-experts-for","title":"MoVEInt: Mixture of Variational Experts for Learning Human-Robot Interactions from Demonstrations","first_author":"Vignesh Prasad","url":null},"license":null,"modalities":[{"name":"3D","url":"/datasets/modality/3d"},{"name":"Tracking","url":"/datasets/modality/tracking"}],"tasks":[{"name":"Human Interaction Recognition","url":"/task/human-interaction-recognition","datasets_with_task":"/datasets/task/human-interaction-recognition"},{"name":"Motion Generation","url":"/task/motion-generation","datasets_with_task":"/datasets/task/motion-generation"},{"name":"Human motion prediction","url":"/task/human-motion-prediction","datasets_with_task":"/datasets/task/human-motion-prediction"}],"languages":[],"variants":["NuiSI 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":"2026-09-24T18:15:14+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."}