{"url":"/dataset/prid2011","name":"PRID2011","full_name":"Person RE-ID 2011","description_markdown":"PRID 2011 is a person reidentification dataset that provides multiple person trajectories recorded from two different static surveillance cameras, monitoring crosswalks and sidewalks. The dataset shows a clean background, and the people in the dataset are rarely occluded. In the dataset, 200 people appear in both views. Among the 200 people, 178 people have more than 20 appearances\r\n\r\nSource: [PaMM: Pose-aware Multi-shot Matching for Improving Person Re-identification](https://arxiv.org/abs/1705.06011)","description_withheld":null,"homepage":"","introduced_date":"2011-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/mask-r-cnn","title":"Mask R-CNN","first_author":"Kaiming He","url":null},"license":null,"modalities":[],"tasks":[{"name":"Person Re-Identification","url":"/task/person-re-identification","datasets_with_task":"/datasets/task/person-re-identification"},{"name":"Unsupervised Person Re-Identification","url":"/task/unsupervised-person-re-identification","datasets_with_task":"/datasets/task/unsupervised-person-re-identification"}],"languages":[],"variants":["PRID2011"],"data_loaders":[{"repo":"https://github.com/Higashiguchi-Shingo/Siamese2","url":"https://github.com/Higashiguchi-Shingo/Siamese2","frameworks":["tf"]}],"num_papers_in_archive":19,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/person-re-identification-on-prid2011","task":"Person Re-Identification","dataset_variant":"PRID2011","rows":13,"metrics":["Rank-1","Rank-20","Rank-5","Rank-10"],"first_row_in_archive_order":{"model":"B-BOT + Attention and CL loss*","paper":"/paper/video-person-re-id-fantastic-techniques-and","metrics":{"Rank-1":"96.6"},"code_links":[{"title":"ppriyank/Video-Person-Re-ID-Fantastic-Techniques-and-Where-to-Find-Them","url":"https://github.com/ppriyank/Video-Person-Re-ID-Fantastic-Techniques-and-Where-to-Find-Them"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/unsupervised-person-re-identification-on-9","task":"Unsupervised Person Re-Identification","dataset_variant":"PRID2011","rows":1,"metrics":[" Rank-1","Rank-5","Rank-20"],"first_row_in_archive_order":{"model":"uPMnet","paper":"/paper/exploiting-robust-unsupervised-video-person","metrics":{" Rank-1":"92.00","Rank-20":"100.0","Rank-5":"97.7"},"code_links":[{"title":"deropty/uPMnet","url":"https://github.com/deropty/uPMnet"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/exploiting-robust-unsupervised-video-person","title":"Exploiting Robust Unsupervised Video Person Re-identification","date":"2021-11-09","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/fine-grained-re-identification","title":"Fine-Grained Re-Identification","date":"2020-11-26","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/video-person-re-id-fantastic-techniques-and","title":"Video Person Re-ID: Fantastic Techniques and Where to Find Them","date":"2019-11-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/adaptive-graph-representation-learning-for","title":"Adaptive Graph Representation Learning for Video Person Re-identification","date":"2019-09-05","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/unsupervised-tracklet-person-re","title":"Unsupervised Tracklet Person Re-Identification","date":"2019-03-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/unsupervised-person-re-identification-by-deep-1","title":"Unsupervised Person Re-identification by Deep Learning Tracklet Association","date":"2018-09-08","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/robust-anchor-embedding-for-unsupervised","title":"Robust Anchor Embedding for Unsupervised Video Person Re-Identification in the Wild","date":"2018-09-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/deep-association-learning-for-unsupervised","title":"Deep Association Learning for Unsupervised Video Person Re-identification","date":"2018-08-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/video-person-re-identification-with","title":"Video Person Re-Identification With Competitive Snippet-Similarity Aggregation and Co-Attentive Snippet Embedding","date":"2018-06-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/domain-adaptation-through-synthesis-for","title":"Domain Adaptation through Synthesis for Unsupervised Person Re-identification","date":"2018-04-26","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/stepwise-metric-promotion-for-unsupervised","title":"Stepwise Metric Promotion for Unsupervised Video Person Re-Identification","date":"2017-10-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/dynamic-label-graph-matching-for-unsupervised","title":"Dynamic Label Graph Matching for Unsupervised Video Re-Identification","date":"2017-09-27","rows_on_this_dataset":2,"code_links":0,"syntology":null}],"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."}