{"url":"/dataset/cid","name":"CID","full_name":"Campus Image Dataset","description_markdown":"The **CID** (**Campus Image Dataset**) is a dataset captured in low-light env with the help of Android programming. Its basic unit is group, which is named by capture time and contains 8 exposure-time-varying raw image shot in a burst.\n\nSource: [https://github.com/505030475/ExtremeLowLight](https://github.com/505030475/ExtremeLowLight)","description_withheld":null,"homepage":"https://github.com/505030475/ExtremeLowLight","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-an-adaptive-model-for-extreme-low","title":"Learning an Adaptive Model for Extreme Low-light Raw Image Processing","first_author":"Qingxu Fu","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Edge Detection","url":"/task/edge-detection","datasets_with_task":"/datasets/task/edge-detection"}],"languages":[],"variants":["CID"],"data_loaders":[{"repo":"https://github.com/505030475/ExtremeLowLight","url":"https://github.com/505030475/ExtremeLowLight","frameworks":["tf"]}],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/edge-detection-on-cid","task":"Edge Detection","dataset_variant":"CID","rows":2,"metrics":["ODS"],"first_row_in_archive_order":{"model":"DexiNed (WACV'2020)","paper":"/paper/dense-extreme-inception-network-towards-a","metrics":{"ODS":"0.65"},"code_links":[{"title":"xavysp/DexiNed","url":"https://github.com/xavysp/DexiNed"},{"title":"a-nau/Plane-Segmentation-Refinement","url":"https://github.com/a-nau/Plane-Segmentation-Refinement"},{"title":"xavysp/MBIPED","url":"https://github.com/xavysp/MBIPED"},{"title":"chaitravi-ce/Edge-Detection-Using-ML","url":"https://github.com/chaitravi-ce/Edge-Detection-Using-ML"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/dense-extreme-inception-network-towards-a","title":"Dense Extreme Inception Network: Towards a Robust CNN Model for Edge Detection","date":"2019-09-04","rows_on_this_dataset":1,"code_links":4,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":19,"samples_ran":1,"samples_unverified":18,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":19,"samples_ran":1,"samples_unverified":18,"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."}