{"url":"/dataset/uhdm","name":"UHDM","full_name":null,"description_markdown":"The first ultra-high-definition image demoireing dataset,  consisting of 4,500 4K resolution training pairs and 500 standard 4K resolution validation pairs.","description_withheld":null,"homepage":"https://xinyu-andy.github.io/uhdm-page/","introduced_date":"2022-07-20","introduced_date_note":null,"introduced_by":{"paper":"/paper/towards-efficient-and-scale-robust-ultra-high","title":"Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing","first_author":"Xin Yu","url":null},"license":null,"modalities":[],"tasks":[{"name":"Image Restoration","url":"/task/image-restoration","datasets_with_task":"/datasets/task/image-restoration"},{"name":"Image Enhancement","url":"/task/image-enhancement","datasets_with_task":"/datasets/task/image-enhancement"}],"languages":[],"variants":["UHDM"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-restoration-on-uhdm","task":"Image Restoration","dataset_variant":"UHDM","rows":2,"metrics":["PSNR"],"first_row_in_archive_order":{"model":"ESDNet-L","paper":"/paper/towards-efficient-and-scale-robust-ultra-high","metrics":{"PSNR":"22.422"},"code_links":[{"title":"CVMI-Lab/UHDM","url":"https://github.com/CVMI-Lab/UHDM"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/towards-efficient-and-scale-robust-ultra-high","title":"Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoireing","date":"2022-07-20","rows_on_this_dataset":2,"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."}