{"url":"/dataset/msu-deinterlacer-benchmark-2020","name":"MSU Deinterlacer Benchmark","full_name":null,"description_markdown":"This is a dataset for video deinterlacing problem. The dataset contains 28 video sequences. Each sequence's length is 60 frames. Resolution of all video sequences is 1920x1080. TFF interlacing was used to get interlaced data from GT.","description_withheld":null,"homepage":"https://videoprocessing.ai/benchmarks/deinterlacer.html","introduced_date":"2020-11-26","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"}],"tasks":[{"name":"Video Deinterlacing","url":"/task/video-deinterlacing","datasets_with_task":"/datasets/task/video-deinterlacing"}],"languages":[],"variants":["MSU Deinterlacer Benchmark"],"data_loaders":[],"num_papers_in_archive":4,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/video-deinterlacing-on-msu-deinterlacer","task":"Video Deinterlacing","dataset_variant":"MSU Deinterlacer Benchmark","rows":31,"metrics":["Subjective","PSNR","SSIM","VMAF","FPS on CPU"],"first_row_in_archive_order":{"model":"MFDIN (L)","paper":"/paper/multi-frame-joint-enhancement-for-early","metrics":{"FPS on CPU":"1.6","PSNR":"43.884","SSIM":"0.979","Subjective":"1.054","VMAF":"97.30"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/multi-field-de-interlacing-using-deformable","title":"Multi-Field De-interlacing using Deformable Convolution Residual Blocks and Self-Attention","date":"2022-09-21","rows_on_this_dataset":3,"code_links":0,"syntology":null},{"paper":"/paper/multi-frame-joint-enhancement-for-early","title":"Multi-frame Joint Enhancement for Early Interlaced Videos","date":"2021-09-29","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/spatial-temporal-correlation-and-topology","title":"Spatial-Temporal Correlation and Topology Learning for Person Re-Identification in Videos","date":"2021-04-15","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/real-time-deep-video-deinterlacing","title":"Real-time Deep Video Deinterlacing","date":"2017-08-01","rows_on_this_dataset":1,"code_links":2,"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."}