{"url":"/dataset/csd","name":"CSD","full_name":"Collaborative SLAM Dataset","description_markdown":"Comprises 4 different subsets - Flat, House, Priory and Lab - each containing a number of different sequences that can be successfully relocalised against each other. \r\n\r\nSource: [CSD](https://github.com/torrvision/CollaborativeSLAMDataset)","description_withheld":null,"homepage":"https://github.com/torrvision/CollaborativeSLAMDataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/collaborative-large-scale-dense-3d","title":"Collaborative Large-Scale Dense 3D Reconstruction with Online Inter-Agent Pose Optimisation","first_author":"Stuart Golodetz","url":null},"license":null,"modalities":[],"tasks":[{"name":"3D Reconstruction","url":"/task/3d-reconstruction","datasets_with_task":"/datasets/task/3d-reconstruction"},{"name":"Single Image Desnowing","url":"/task/single-image-desnowing","datasets_with_task":"/datasets/task/single-image-desnowing"}],"languages":[],"variants":["CSD"],"data_loaders":[{"repo":"https://github.com/torrvision/CollaborativeSLAMDataset","url":"https://github.com/torrvision/CollaborativeSLAMDataset","frameworks":[]}],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/single-image-desnowing-on-csd","task":"Single Image Desnowing","dataset_variant":"CSD","rows":6,"metrics":["Average PSNR (dB)"],"first_row_in_archive_order":{"model":"Instruct-IPT","paper":"/paper/instruct-ipt-all-in-one-image-processing-1","metrics":{"Average PSNR (dB)":"40.12"},"code_links":[{"title":"huawei-noah/Pretrained-IPT","url":"https://github.com/huawei-noah/Pretrained-IPT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/instruct-ipt-all-in-one-image-processing-1","title":"Instruct-IPT: All-in-One Image Processing Transformer via Weight Modulation","date":"2024-06-30","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/snowformer-scale-aware-transformer-via","title":"SnowFormer: Context Interaction Transformer with Scale-awareness for Single Image Desnowing","date":"2022-08-20","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":6,"samples_unverified":5,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/simple-baselines-for-image-restoration","title":"Simple Baselines for Image Restoration","date":"2022-04-10","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":30,"samples_ran":23,"samples_unverified":7,"pointer_only_for_licence":17,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/restormer-efficient-transformer-for-high","title":"Restormer: Efficient Transformer for High-Resolution Image Restoration","date":"2021-11-18","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":4,"samples_unverified":0,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/uformer-a-general-u-shaped-transformer-for","title":"Uformer: A General U-Shaped Transformer for Image Restoration","date":"2021-06-06","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":6,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/all-snow-removed-single-image-desnowing","title":"ALL Snow Removed: Single Image Desnowing Algorithm Using Hierarchical Dual-Tree Complex Wavelet Representation and Contradict Channel Loss","date":"2021-01-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":51,"samples_ran":39,"samples_unverified":12,"pointer_only_for_licence":34,"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."}