{"url":"/dataset/mit-traffic","name":"MIT Traffic","full_name":"MIT Traffic","description_markdown":"**MIT Traffic** is a dataset for research on activity analysis and crowded scenes. It includes a traffic video sequence of 90 minutes long. It is recorded by a stationary camera. The size of the scene is 720 by 480 and it is divided into 20 clips.\r\n\r\nSource: [MIT Traffic Dataset](http://mmlab.ie.cuhk.edu.hk/datasets/mit_traffic/index.html)","description_withheld":null,"homepage":"http://mmlab.ie.cuhk.edu.hk/datasets/mit_traffic/index.html","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":null,"title":"Unsupervised Activity Perception in Crowded and Complicated Scenes Using Hierarchical Bayesian Models","first_author":null,"url":"https://ieeexplore.ieee.org/document/4731265"},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["MIT Traffic"],"data_loaders":[{"repo":"https://github.com/vis-opt-group/sci","url":"https://github.com/vis-opt-group/sci","frameworks":["pytorch"]}],"num_papers_in_archive":6,"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."}