{"url":"/dataset/cfc-daod","name":"CFC-DAOD","full_name":"Caltech Fish Counting – Domain Adaptive Object Detection","description_markdown":"CFC-DAOD is a domain adaptation extension to the [Caltech Fish Counting](https://paperswithcode.com/dataset/cfc) domain generalization benchmark.\r\n\r\nThe goal is cross-domain object detection of a single class, \"fish\", in sonar videos. The source domain consists of data from one river, Kenai, and the target domain consists of data from another out-of-domain river, Channel. CFC-DAOD introduces new data from the target domain to be used for unsupervised domain adaptive object detection: 168k bounding box annotations in 29k frames sampled from 150 new videos captured over two days from 3 different sensors on the Channel river.","description_withheld":null,"homepage":"https://github.com/visipedia/caltech-fish-counting/tree/main/CFC-DAOD","introduced_date":"2024-03-18","introduced_date_note":null,"introduced_by":{"paper":"/paper/align-and-distill-unifying-and-improving","title":"Align and Distill: Unifying and Improving Domain Adaptive Object Detection","first_author":"Justin Kay","url":null},"license":{"name":"MIT","url":"https://github.com/visipedia/caltech-fish-counting/blob/main/CFC-DAOD/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Unsupervised Domain Adaptation","url":"/task/unsupervised-domain-adaptation","datasets_with_task":"/datasets/task/unsupervised-domain-adaptation"}],"languages":[],"variants":["CFC-DAOD"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/unsupervised-domain-adaptation-on-cfc-daod","task":"Unsupervised Domain Adaptation","dataset_variant":"CFC-DAOD","rows":6,"metrics":["AP@0.5"],"first_row_in_archive_order":{"model":"ALDI++ (ResNet50-FPN)","paper":"/paper/align-and-distill-unifying-and-improving","metrics":{"AP@0.5":"76.1"},"code_links":[{"title":"justinkay/aldi","url":"https://github.com/justinkay/aldi"},{"title":"estrellaxyu/differential-alignment-for-daod","url":"https://github.com/estrellaxyu/differential-alignment-for-daod"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/align-and-distill-unifying-and-improving","title":"Align and Distill: Unifying and Improving Domain Adaptive Object Detection","date":"2024-03-18","rows_on_this_dataset":6,"code_links":2,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}