{"url":"/dataset/pirm","name":"PIRM","full_name":"Perceptual Image Restoration and Manipulation","description_markdown":"The PIRM dataset consists of 200 images, which are divided into two equal sets for validation and testing. These images cover diverse contents, including people, objects, environments, flora, natural scenery, etc. Images vary in size, and are typically ~300K pixels in resolution.","description_withheld":null,"homepage":"https://pirm.github.io","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/the-2018-pirm-challenge-on-perceptual-image","title":"The 2018 PIRM Challenge on Perceptual Image Super-resolution","first_author":"Yochai Blau","url":null},"license":{"name":"CC BY-NC-SA 4.0","url":"https://creativecommons.org/licenses/by-nc-sa/4.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Super-Resolution","url":"/task/image-super-resolution","datasets_with_task":"/datasets/task/image-super-resolution"},{"name":"Image Restoration","url":"/task/image-restoration","datasets_with_task":"/datasets/task/image-restoration"}],"languages":[],"variants":["PIRM-test","PIRM"],"data_loaders":[{"repo":"https://github.com/eugenesiow/super-image-data","url":"https://github.com/eugenesiow/super-image-data","frameworks":["pytorch"]}],"num_papers_in_archive":32,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-super-resolution-on-pirm-test","task":"Image Super-Resolution","dataset_variant":"PIRM-test","rows":3,"metrics":["NIQE"],"first_row_in_archive_order":{"model":"RankSRGAN","paper":"/paper/ranksrgan-generative-adversarial-networks","metrics":{"NIQE":"2.51"},"code_links":[{"title":"xpixelgroup/ranksrgan","url":"https://github.com/xpixelgroup/ranksrgan"},{"title":"WenlongZhang0724/RankSRGAN","url":"https://github.com/WenlongZhang0724/RankSRGAN"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/ranksrgan-generative-adversarial-networks","title":"RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution","date":"2019-08-18","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/esrgan-enhanced-super-resolution-generative","title":"ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks","date":"2018-09-01","rows_on_this_dataset":1,"code_links":46,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":44,"samples_ran":8,"samples_unverified":36,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/photo-realistic-single-image-super-resolution","title":"Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network","date":"2016-09-15","rows_on_this_dataset":1,"code_links":140,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":72,"samples_ran":16,"samples_unverified":56,"pointer_only_for_licence":11,"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":2,"samples_harvested":116,"samples_ran":24,"samples_unverified":92,"pointer_only_for_licence":11,"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."}