{"url":"/dataset/amuse","name":"AMUSE","full_name":"Automotive Multi-Sensor Dataset","description_markdown":"The automotive multi-sensor (AMUSE) dataset consists of inertial and other complementary sensor data combined with monocular, omnidirectional, high frame rate visual data taken in real traffic scenes during multiple test drives.\r\n\r\nPaper: [A Multi-sensor Traffic Scene Dataset with Omnidirectional Video](https://doi.org/10.1109/CVPRW.2013.110)\r\n\r\nSource: [AMUSE](http://www.cvl.isy.liu.se/en/research/datasets/amuse/)\r\n\r\nImage Source: [AMUSE](http://www.cvl.isy.liu.se/en/research/datasets/amuse/)","description_withheld":null,"homepage":"http://www.cvl.isy.liu.se/en/research/datasets/amuse/","introduced_date":"2013-06-01","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["AMUSE"],"data_loaders":[],"num_papers_in_archive":0,"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."}