{"url":"/dataset/sen12ms-cr-ts","name":"SEN12MS-CR-TS","full_name":"SEN12MS-CR-TS","description_markdown":"**SEN12MS-CR-TS** is a multi-modal and multi-temporal data set for cloud removal. It contains time-series of paired and co-registered Sentinel-1 and cloudy as well as cloud-free Sentinel-2 data from European Space Agency's Copernicus mission. Each time series contains 30 cloudy and clear observations regularly sampled throughout the year 2018. Our multi-temporal data set is readily pre-processed and backward-compatible with [SEN12MS-CR](https://paperswithcode.com/dataset/sen12ms-cr).","description_withheld":null,"homepage":"https://patricktum.github.io/cloud_removal/","introduced_date":"2022-01-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/sen12ms-cr-ts-a-remote-sensing-data-set-for","title":"SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal","first_author":"Patrick Ebel","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Time series","url":"/datasets/modality/time-series"},{"name":"Hyperspectral images","url":"/datasets/modality/hyperspectral-images"}],"tasks":[{"name":"Image-to-Image Translation","url":"/task/image-to-image-translation","datasets_with_task":"/datasets/task/image-to-image-translation"},{"name":"Image Reconstruction","url":"/task/image-reconstruction","datasets_with_task":"/datasets/task/image-reconstruction"},{"name":"Image Denoising","url":"/task/image-denoising","datasets_with_task":"/datasets/task/image-denoising"},{"name":"Image Dehazing","url":"/task/image-dehazing","datasets_with_task":"/datasets/task/image-dehazing"},{"name":"Video Reconstruction","url":"/task/video-reconstruction","datasets_with_task":"/datasets/task/video-reconstruction"},{"name":"Cloud Removal","url":"/task/cloud-removal","datasets_with_task":"/datasets/task/cloud-removal"}],"languages":[],"variants":["SEN12MS-CR-TS"],"data_loaders":[{"repo":"https://github.com/PatrickTUM/SEN12MS-CR-TS","url":"https://github.com/PatrickTUM/SEN12MS-CR-TS","frameworks":["pytorch"]}],"num_papers_in_archive":7,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/cloud-removal-on-sen12ms-cr-ts","task":"Cloud Removal","dataset_variant":"SEN12MS-CR-TS","rows":7,"metrics":["RMSE","PSNR","SSIM","SAM"],"first_row_in_archive_order":{"model":"SeqDMs","paper":"/paper/cloud-removal-in-remote-sensing-using","metrics":{"PSNR":"28.07","RMSE":"0.045","SAM":"12.777","SSIM":"0.827"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/cloud-removal-in-remote-sensing-using","title":"Cloud Removal in Remote Sensing Using Sequential-Based Diffusion Models","date":"2023-05-31","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/uncrtaints-uncertainty-quantification-for","title":"UnCRtainTS: Uncertainty Quantification for Cloud Removal in Optical Satellite Time Series","date":"2023-04-11","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/sen12ms-cr-ts-a-remote-sensing-data-set-for","title":"SEN12MS-CR-TS: A Remote Sensing Data Set for Multi-modal Multi-temporal Cloud Removal","date":"2022-01-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/panoptic-segmentation-of-satellite-image-time","title":"Panoptic Segmentation of Satellite Image Time Series with Convolutional Temporal Attention Networks","date":"2021-07-16","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":11,"samples_ran":10,"samples_unverified":1,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cloud-removal-in-sentinel-2-imagery-using-a","title":"Cloud removal in Sentinel-2 imagery using a deep residual neural network and SAR-optical data fusion","date":"2020-07-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/cloud-removal-in-satellite-images-using","title":"Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks","date":"2019-12-14","rows_on_this_dataset":1,"code_links":3,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":11,"samples_ran":10,"samples_unverified":1,"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."}