{"url":"/dataset/occluded-reid","name":"Occluded REID","full_name":"Occluded REID","description_markdown":"**Occluded REID** is an occluded person dataset captured by mobile cameras, consisting of 2,000 images of 200 occluded persons (see Fig. (c)). Each identity has 5 full-body person images and 5 occluded person images with different types of occlusion.\r\n\r\nSource: [Foreground-aware Pyramid Reconstruction for Alignment-free Occluded Person Re-identification](https://arxiv.org/abs/1904.04975)\r\nImage Source: [https://github.com/tinajia2012/ICME2018_Occluded-Person-Reidentification_datasets](https://github.com/tinajia2012/ICME2018_Occluded-Person-Reidentification_datasets)","description_withheld":null,"homepage":"https://github.com/tinajia2012/ICME2018_Occluded-Person-Reidentification_datasets","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/occluded-person-re-identification","title":"Occluded Person Re-identification","first_author":"Jiaxuan Zhuo","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Person Re-Identification","url":"/task/person-re-identification","datasets_with_task":"/datasets/task/person-re-identification"},{"name":"Semantic Parsing","url":"/task/semantic-parsing","datasets_with_task":"/datasets/task/semantic-parsing"},{"name":"Graph Matching","url":"/task/graph-matching","datasets_with_task":"/datasets/task/graph-matching"}],"languages":[],"variants":["Occluded REID"],"data_loaders":[{"repo":"https://github.com/tinajia2012/ICME2018_Occluded-Person-Reidentification_datasets","url":"https://github.com/tinajia2012/ICME2018_Occluded-Person-Reidentification_datasets","frameworks":[]}],"num_papers_in_archive":65,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/person-re-identification-on-occluded-reid-1","task":"Person Re-Identification","dataset_variant":"Occluded REID","rows":5,"metrics":["mAP","Rank-1"],"first_row_in_archive_order":{"model":"KPR + Pose2ID (no RK)","paper":"/paper/from-poses-to-identity-training-free-person","metrics":{"Rank-1":"91.00","mAP":"89.34"},"code_links":[{"title":"yuanc3/Pose2ID","url":"https://github.com/yuanc3/Pose2ID"},{"title":"yuanc3/dmon-aro","url":"https://github.com/yuanc3/dmon-aro"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/from-poses-to-identity-training-free-person","title":"From Poses to Identity: Training-Free Person Re-Identification via Feature Centralization","date":"2025-03-02","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/keypoint-promptable-re-identification","title":"Keypoint Promptable Re-Identification","date":"2024-07-25","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/body-part-based-representation-learning-for","title":"Body Part-Based Representation Learning for Occluded Person Re-Identification","date":"2022-11-07","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/feature-erasing-and-diffusion-network-for","title":"Feature Erasing and Diffusion Network for Occluded Person Re-Identification","date":"2021-12-16","rows_on_this_dataset":1,"code_links":1,"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."}