{"url":"/dataset/eorssd","name":"EORSSD","full_name":"Extended Optical Remote Sensing Saliency Detection","description_markdown":"The **Extended Optical Remote Sensing Saliency Detection** (**EORSSD**) dataset is an extension of the ORSSD dataset. This new dataset is larger and more varied than the original. It contains 2,000 images and corresponding pixel-wise ground truth, which includes many semantically meaningful but challenging images.\r\n\r\nSource: [https://github.com/rmcong/EORSSD-dataset](https://github.com/rmcong/EORSSD-dataset)\r\nImage Source: [Zhang et al](https://arxiv.org/pdf/2011.13144v1.pdf)","description_withheld":null,"homepage":"https://github.com/rmcong/EORSSD-dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/dense-attention-fluid-network-for-salient","title":"Dense Attention Fluid Network for Salient Object Detection in Optical Remote Sensing Images","first_author":"Qijian Zhang","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Salient Object Detection","url":"/task/salient-object-detection-1","datasets_with_task":"/datasets/task/salient-object-detection-1"}],"languages":[],"variants":["EORSSD"],"data_loaders":[{"repo":"https://github.com/rmcong/EORSSD-dataset","url":"https://github.com/rmcong/EORSSD-dataset","frameworks":[]}],"num_papers_in_archive":20,"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."}