{"url":"/dataset/mhp","name":"MHP","full_name":"Multiple-Human Parsing","description_markdown":"The MHP dataset contains multiple persons captured in real-world scenes with pixel-level fine-grained semantic annotations in an instance-aware setting.\r\n\r\nSource: [Multiple-Human Parsing in the Wild](https://arxiv.org/pdf/1705.07206)\r\nImage Source: [Li et al](https://arxiv.org/pdf/1705.07206.pdf)","description_withheld":null,"homepage":"https://arxiv.org/pdf/1705.07206.pdf","introduced_date":"2017-05-19","introduced_date_note":null,"introduced_by":{"paper":"/paper/multiple-human-parsing-in-the-wild","title":"Multiple-Human Parsing in the Wild","first_author":"Jianshu Li","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"},{"name":"Human Part Segmentation","url":"/task/human-part-segmentation","datasets_with_task":"/datasets/task/human-part-segmentation"},{"name":"Human Parsing","url":"/task/human-parsing","datasets_with_task":"/datasets/task/human-parsing"},{"name":"Multi-Human Parsing","url":"/task/multi-human-parsing","datasets_with_task":"/datasets/task/multi-human-parsing"}],"languages":[],"variants":["MHP","MHP v2.0","MHP v1.0"],"data_loaders":[{"repo":"https://github.com/open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose/blob/master/docs/tasks/2d_body_keypoint.md#mhp","frameworks":["pytorch"]}],"num_papers_in_archive":14,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-human-parsing-on-mhp-v20","task":"Multi-Human Parsing","dataset_variant":"MHP v2.0","rows":5,"metrics":["AP 0.5"],"first_row_in_archive_order":{"model":"UniParser","paper":"/paper/uniparser-multi-human-parsing-with-unified","metrics":{"AP 0.5":"51.2"},"code_links":[{"title":"cjm-sfw/Uniparser","url":"https://github.com/cjm-sfw/Uniparser"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-human-parsing-on-mhp-v10","task":"Multi-Human Parsing","dataset_variant":"MHP v1.0","rows":4,"metrics":["AP 0.5"],"first_row_in_archive_order":{"model":"NAN","paper":"/paper/understanding-humans-in-crowded-scenes-deep","metrics":{"AP 0.5":"57.09%"},"code_links":[{"title":"open-mmlab/mmpose","url":"https://github.com/open-mmlab/mmpose"},{"title":"ZhaoJ9014/Multi-Human-Parsing","url":"https://github.com/ZhaoJ9014/Multi-Human-Parsing"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/human-part-segmentation-on-mhp-v20","task":"Human Part Segmentation","dataset_variant":"MHP v2.0","rows":1,"metrics":["Mean IoU"],"first_row_in_archive_order":{"model":"Parsing R-CNN + ResNext101","paper":"/paper/parsing-r-cnn-for-instance-level-human","metrics":{"Mean IoU":"41.8"},"code_links":[{"title":"soeaver/Parsing-R-CNN","url":"https://github.com/soeaver/Parsing-R-CNN"},{"title":"soeaver/RP-R-CNN","url":"https://github.com/soeaver/RP-R-CNN"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/uniparser-multi-human-parsing-with-unified","title":"UniParser: Multi-Human Parsing with Unified Correlation Representation Learning","date":"2023-10-13","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/single-stage-multi-human-parsing-via-point","title":"Single-stage Multi-human Parsing via Point Sets and Center-based Offsets","date":"2023-04-22","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/parsing-r-cnn-for-instance-level-human","title":"Parsing R-CNN for Instance-Level Human Analysis","date":"2018-11-30","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":7,"samples_ran":2,"samples_unverified":5,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/understanding-humans-in-crowded-scenes-deep","title":"Understanding Humans in Crowded Scenes: Deep Nested Adversarial Learning and A New Benchmark for Multi-Human Parsing","date":"2018-04-10","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/semantic-instance-segmentation-with-a","title":"Semantic Instance Segmentation with a Discriminative Loss Function","date":"2017-08-08","rows_on_this_dataset":1,"code_links":8,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":0,"samples_unverified":2,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multiple-human-parsing-in-the-wild","title":"Multiple-Human Parsing in the Wild","date":"2017-05-19","rows_on_this_dataset":2,"code_links":2,"syntology":null},{"paper":"/paper/mask-r-cnn","title":"Mask R-CNN","date":"2017-03-20","rows_on_this_dataset":2,"code_links":179,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":140,"samples_ran":42,"samples_unverified":98,"pointer_only_for_licence":23,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":3,"samples_harvested":149,"samples_ran":44,"samples_unverified":105,"pointer_only_for_licence":25,"papers_with_no_sample_that_ran":1,"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."}