{"url":"/dataset/bs-rsc","name":"BS-RSC","full_name":null,"description_markdown":"BS-RSC is a real-world rolling shutter (RS) correction dataset and a corresponding model to correct the RS frames in a distorted video. Real distorted videos with corresponding ground truth are recorded simultaneously via a well-designed beam-splitter-based acquisition system. BSRSC contains various motions of both camera and objects in dynamic scenes.","description_withheld":null,"homepage":"https://github.com/ljzycmd/BSRSC","introduced_date":"2022-04-29","introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-adaptive-warping-for-real-world","title":"Learning Adaptive Warping for Real-World Rolling Shutter Correction","first_author":"Mingdeng Cao","url":null},"license":{"name":"MIT","url":"https://github.com/ljzycmd/BSRSC/blob/main/LICENSE"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Video Restoration","url":"/task/video-restoration","datasets_with_task":"/datasets/task/video-restoration"},{"name":"Rolling Shutter Correction","url":"/task/unrolling","datasets_with_task":"/datasets/task/unrolling"}],"languages":[],"variants":["BS-RSC"],"data_loaders":[],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/rolling-shutter-correction-on-bs-rsc","task":"Rolling Shutter Correction","dataset_variant":"BS-RSC","rows":8,"metrics":["Average PSNR (dB)"],"first_row_in_archive_order":{"model":"DFRSC-3Frames","paper":"/paper/rolling-shutter-correction-with-intermediate","metrics":{"Average PSNR (dB)":"34.48"},"code_links":[{"title":"ljzycmd/dfrsc","url":"https://github.com/ljzycmd/dfrsc"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/rolling-shutter-correction-with-intermediate","title":"Rolling Shutter Correction with Intermediate Distortion Flow Estimation","date":"2024-04-09","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":3,"samples_unverified":1,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/towards-nonlinear-motion-aware-and-occlusion","title":"Towards Nonlinear-Motion-Aware and Occlusion-Robust Rolling Shutter Correction","date":"2023-03-31","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/joint-appearance-and-motion-learning-for","title":"Joint Appearance and Motion Learning for Efficient Rolling Shutter Correction","date":"2023-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-adaptive-warping-for-real-world","title":"Learning Adaptive Warping for Real-World Rolling Shutter Correction","date":"2022-04-29","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/sunet-symmetric-undistortion-network-for","title":"SUNet: Symmetric Undistortion Network for Rolling Shutter Correction","date":"2021-08-10","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/towards-rolling-shutter-correction-and","title":"Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes","date":"2021-04-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/deep-shutter-unrolling-network","title":"Deep Shutter Unrolling Network","date":"2020-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":7,"samples_ran":5,"samples_unverified":2,"pointer_only_for_licence":4,"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."}