{"url":"/dataset/ahp","name":"AHP","full_name":"Amodal Human Perception","description_markdown":"The AHP dataset consists of 56,599 images in total which are collected from several large-scale instance segmentation and detection datasets, including COCO, VOC (w/ SBD), LIP, Objects365 and OpenImages. Each image is annotated with a pixel-level segmentation mask of a single integrated human.\r\n\r\nThe dataset is initially proposed to solve the task of human de-occlusion.\r\n#####Data Splits\r\n\r\n* Train: Totally 56,302 images with annotations of integrated humans.\r\n* Valid: Totally 297 images of synthesized occlusion cases.\r\n* Test: Totally 56 images of artificial occlusion cases.","description_withheld":null,"homepage":"https://sydney0zq.github.io/ahp/","introduced_date":"2021-03-22","introduced_date_note":null,"introduced_by":{"paper":"/paper/human-de-occlusion-invisible-perception-and","title":"Human De-occlusion: Invisible Perception and Recovery for Humans","first_author":"Qiang Zhou","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["AHP"],"data_loaders":[],"num_papers_in_archive":5,"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."}