{"url":"/dataset/tinyperson","name":"TinyPerson","full_name":null,"description_markdown":"**TinyPerson** is a benchmark for tiny object detection in a long distance and with massive backgrounds. The images in TinyPerson are collected from the Internet. First, videos with a high resolution are collected from different websites. Second, images from the video are sampled every 50 frames. Then images with a certain repetition (homogeneity) are deleted, and the resulting images are annotated with 72,651 objects with bounding boxes by hand.\r\n\r\nSource: [https://arxiv.org/abs/1912.10664](https://arxiv.org/abs/1912.10664)\r\nImage Source: [https://arxiv.org/pdf/1912.10664.pdf](https://arxiv.org/pdf/1912.10664.pdf)","description_withheld":null,"homepage":"http://vision.ucas.ac.cn/resource.asp","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/scale-match-for-tiny-person-detection","title":"Scale Match for Tiny Person Detection","first_author":"Xuehui Yu","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Image Restoration","url":"/task/image-restoration","datasets_with_task":"/datasets/task/image-restoration"},{"name":"Human Detection","url":"/task/human-detection","datasets_with_task":"/datasets/task/human-detection"}],"languages":[],"variants":["TinyPerson"],"data_loaders":[],"num_papers_in_archive":25,"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":"2026-09-25T09:33:49+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."}