{"url":"/dataset/fmars","name":"FMARS","full_name":"Foundation Models Annotation in Remote Sensing","description_markdown":"FMARS is a large-scale dataset of Very High Resolution (VHR) remote sensing images with annotations generated using Vision Foundation Models. The dataset focuses on disaster management applications and provides pre-event imagery and annotations for major crisis events worldwide from 2021 to 2023.","description_withheld":null,"homepage":"https://huggingface.co/datasets/links-ads/fmars-dataset","introduced_date":"2024-05-30","introduced_date_note":null,"introduced_by":{"paper":"/paper/fmars-annotating-remote-sensing-images-for","title":"FMARS: Annotating Remote Sensing Images for Disaster Management using Foundation Models","first_author":"Edoardo Arnaudo","url":null},"license":{"name":"MIT","url":"https://choosealicense.com/licenses/mit/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Segmentation","url":"/task/image-segmentation","datasets_with_task":"/datasets/task/image-segmentation"},{"name":"Object Detection In Aerial Images","url":"/task/object-detection-in-aerial-images","datasets_with_task":"/datasets/task/object-detection-in-aerial-images"}],"languages":[],"variants":["FMARS"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}