{"url":"/dataset/ciona17","name":"Ciona17","full_name":null,"description_markdown":"Ciona17 is a semantic segmentation dataset with pixel-level annotations pertaining to invasive species in a marine environment. Diverse outdoor illumination, a range of object shapes, colour, and severe occlusion provide a significant real world challenge for the computer vision community. \r\n\r\nSource: [The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment](https://arxiv.org/pdf/1702.05564)\r\nImage Source: [Galloway et al](https://arxiv.org/pdf/1702.05564)","description_withheld":null,"homepage":"https://arxiv.org/pdf/1702.05564.pdf","introduced_date":"2017-02-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-ciona17-dataset-for-semantic-segmentation","title":"The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment","first_author":"Angus Galloway","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Semantic Segmentation","url":"/task/semantic-segmentation","datasets_with_task":"/datasets/task/semantic-segmentation"}],"languages":[],"variants":["Ciona17"],"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."}