{"url":"/dataset/exdark","name":"ExDark","full_name":"Exclusively Dark Image Dataset","description_markdown":"The **Exclusively Dark** (ExDARK) dataset is a collection of 7,363 low-light images from very low-light environments to twilight (i.e 10 different conditions) with 12 object classes (similar to PASCAL VOC) annotated on both image class level and local object bounding boxes.\n\nSource: [https://github.com/cs-chan/Exclusively-Dark-Image-Dataset](https://github.com/cs-chan/Exclusively-Dark-Image-Dataset)","description_withheld":null,"homepage":"https://github.com/cs-chan/Exclusively-Dark-Image-Dataset","introduced_date":null,"introduced_date_note":null,"introduced_by":{"paper":"/paper/getting-to-know-low-light-images-with-the","title":"Getting to Know Low-light Images with The Exclusively Dark Dataset","first_author":"Yuen Peng Loh","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Image Enhancement","url":"/task/image-enhancement","datasets_with_task":"/datasets/task/image-enhancement"},{"name":"Low-Light Image Enhancement","url":"/task/low-light-image-enhancement","datasets_with_task":"/datasets/task/low-light-image-enhancement"}],"languages":[],"variants":["ExDark"],"data_loaders":[{"repo":"https://github.com/cs-chan/Exclusively-Dark-Image-Dataset","url":"https://github.com/cs-chan/Exclusively-Dark-Image-Dataset","frameworks":[]}],"num_papers_in_archive":58,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/2d-object-detection-on-exdark","task":"2D Object Detection","dataset_variant":"ExDark","rows":3,"metrics":["mAP"],"first_row_in_archive_order":{"model":"EMV-YOLO","paper":"/paper/toward-highly-efficient-semantic-guided","metrics":{"mAP":"79.7"},"code_links":[{"title":"Zeng555/EMV-YOLO","url":"https://github.com/Zeng555/EMV-YOLO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-detection-on-exdark-1","task":"Object Detection","dataset_variant":"ExDark","rows":1,"metrics":["mAP"],"first_row_in_archive_order":{"model":"EMV-YOLO","paper":"/paper/toward-highly-efficient-semantic-guided","metrics":{"mAP":"79.7%"},"code_links":[{"title":"Zeng555/EMV-YOLO","url":"https://github.com/Zeng555/EMV-YOLO"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/toward-highly-efficient-semantic-guided","title":"Toward Highly Efficient Semantic-Guided Machine Vision for Low-Light Object Detection","date":"2024-12-20","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/warlearn-weather-adaptive-representation","title":"WARLearn: Weather-Adaptive Representation Learning","date":"2024-11-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multitask-aet-with-orthogonal-tangent-1","title":"Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection","date":"2022-05-06","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":1,"samples_unverified":3,"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":4,"samples_ran":1,"samples_unverified":3,"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."}