{"url":"/dataset/aut-vi","name":"AUT-VI","full_name":"Amirkabir campus dataset","description_markdown":"AUT-VI is a super-challenging visual inertial dataset with 126 diverse sequences in 17 locations. This dataset contains dynamic objects, challenging loop-closure/map-reuse, different lighting conditions, reflections, and sudden camera movements to cover all extreme navigation scenarios. Moreover, the Android application for data capture is released to the public to support ongoing development efforts. \r\nThis dataset aims to exploit the remaining challenges in VIO algorithms, in the hope of improving them to facilitate navigation for visually impaired individuals in both indoor and outdoor settings.","description_withheld":null,"homepage":"https://a3dv.github.io/autvi","introduced_date":"2024-01-07","introduced_date_note":null,"introduced_by":{"paper":"/paper/amirkabir-campus-dataset-real-world","title":"Amirkabir campus dataset: Real-world challenges and scenarios of Visual Inertial Odometry (VIO) for visually impaired people","first_author":"Ali Samadzadeh","url":null},"license":null,"modalities":[],"tasks":[{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Visual Odometry","url":"/task/visual-odometry","datasets_with_task":"/datasets/task/visual-odometry"},{"name":"Loop Closure Detection","url":"/task/loop-closure-detection","datasets_with_task":"/datasets/task/loop-closure-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["AUT-VI"],"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."}