{"url":"/dataset/tinyvirat-v2","name":"TinyVIRAT-v2","full_name":null,"description_markdown":"**TinyVIRAT-v2** is a benchmark dataset for recognizing real-world low-resolution activities present in videos. The dataset is comprised of naturally occuring low-resolution actions. This is an extension of the TinyVIRAT dataset and consists of actions with multiple labels. The videos are extracted from security videos which makes them realistic and more challenging.","description_withheld":null,"homepage":"https://www.crcv.ucf.edu/tiny-actions-challenge-cvpr2021/#tabtwo","introduced_date":"2021-07-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/tinyaction-challenge-recognizing-real-world","title":"TinyAction Challenge: Recognizing Real-world Low-resolution Activities in Videos","first_author":"Praveen Tirupattur","url":null},"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Action Recognition","url":"/task/action-recognition-in-videos","datasets_with_task":"/datasets/task/action-recognition-in-videos"}],"languages":[],"variants":["TinyVIRAT-v2"],"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."}