{"url":"/dataset/uoftped50","name":"UofTPed50","full_name":null,"description_markdown":"**UofTPed50** is an object detection and tracking dataset which uses GPS to ground truth the position and velocity of a pedestrian.\r\n\r\nIt can be used for benchmarking the positional accuracy of 3D pedestrian detection. It contains accurate positioning information by attaching a GPS system to the pedestrian itself. This dataset consists of 50 sequences of varying distance, pedestrian trajectory, and ego-vehicle trajectory. Each sequence contains one pedestrian. The scenarios are broken into four groups.","description_withheld":null,"homepage":"http://autodrive.utoronto.ca/uoftped50","introduced_date":"2019-05-21","introduced_date_note":null,"introduced_by":{"paper":null,"title":"aUToTrack: A Lightweight Object Detection and Tracking System for the SAE AutoDrive Challenge","first_author":null,"url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"LiDAR","url":"/datasets/modality/lidar"}],"tasks":[{"name":"Pedestrian Detection","url":"/task/pedestrian-detection","datasets_with_task":"/datasets/task/pedestrian-detection"}],"languages":[],"variants":["UofTPed50"],"data_loaders":[],"num_papers_in_archive":2,"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."}