{"url":"/dataset/vi-fi-multi-modal-dataset","name":"Vi-Fi Multi-modal Dataset","full_name":null,"description_markdown":"A large-scale multi-modal dataset to facilitate research and studies that concentrate on vision-wireless systems.\r\nThe Vi-Fi dataset is a large-scale multi-modal dataset that consists of vision, wireless and smartphone motion sensor data of multiple participants and passer-by pedestrians in both indoor and outdoor scenarios. In Vi-Fi, vision modality includes RGB-D video from a mounted camera. Wireless modality comprises smartphone data from participants including WiFi FTM and IMU measurements.\r\n\r\nThe presence of Vi-Fi dataset facilitates and innovates multi-modal system research, especially, vision-wireless sensor data fusion, association and localization.\r\n\r\n(Data collection was in accordance with IRB protocols and subject faces have been blurred for subject privacy.)","description_withheld":null,"homepage":"https://sites.google.com/winlab.rutgers.edu/vi-fidataset/home","introduced_date":"2022-05-04","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Time series","url":"/datasets/modality/time-series"},{"name":"RGB-D","url":"/datasets/modality/rgb-d"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"}],"tasks":[{"name":"Multimodal Association","url":"/task/multimodal-association","datasets_with_task":"/datasets/task/multimodal-association"},{"name":"Out-of-Sight Trajectory Prediction","url":"/task/out-of-sight-trajectory-prediction","datasets_with_task":"/datasets/task/out-of-sight-trajectory-prediction"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Vi-Fi Multi-modal Dataset"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/out-of-sight-trajectory-prediction-on-vi-fi","task":"Out-of-Sight Trajectory Prediction","dataset_variant":"Vi-Fi Multi-modal Dataset","rows":6,"metrics":["MSE-D","MSE-P","SUM"],"first_row_in_archive_order":{"model":"OOSTraj","paper":"/paper/oostraj-out-of-sight-trajectory-prediction","metrics":{"MSE-D":"13.42","MSE-P":"13.83","SUM":"27.24"},"code_links":[{"title":"hai-chao-zhang/oostraj","url":"https://github.com/hai-chao-zhang/oostraj"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/oostraj-out-of-sight-trajectory-prediction","title":"OOSTraj: Out-of-Sight Trajectory Prediction With Vision-Positioning Denoising","date":"2024-04-02","rows_on_this_dataset":6,"code_links":1,"syntology":null}],"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."}