{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/the-caltech-fish-counting-dataset-a-benchmark","title":"The Caltech Fish Counting Dataset: A Benchmark for Multiple-Object Tracking and Counting","arxiv_id":"2207.09295","date":"2022-07-19","proceeding":null,"authors":["Justin Kay","Peter Kulits","Suzanne Stathatos","Siqi Deng","Erik Young","Sara Beery","Grant van Horn","Pietro Perona"],"abstract":"We present the Caltech Fish Counting Dataset (CFC), a large-scale dataset for detecting, tracking, and counting fish in sonar videos. We identify sonar videos as a rich source of data for advancing low signal-to-noise computer vision applications and tackling domain generalization in multiple-object tracking (MOT) and counting. In comparison to existing MOT and counting datasets, which are largely restricted to videos of people and vehicles in cities, CFC is sourced from a natural-world domain where targets are not easily resolvable and appearance features cannot be easily leveraged for target re-identification. With over half a million annotations in over 1,500 videos sourced from seven different sonar cameras, CFC allows researchers to train MOT and counting algorithms and evaluate generalization performance at unseen test locations. We perform extensive baseline experiments and identify key challenges and opportunities for advancing the state of the art in generalization in MOT and counting.","url_abs":"https://arxiv.org/abs/2207.09295v1","url_pdf":"https://arxiv.org/pdf/2207.09295v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"the-caltech-fish-counting-dataset-a-benchmark","repo_url":"https://github.com/visipedia/caltech-fish-counting","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"domain-generalization","task_name":"Domain Generalization"},{"task_slug":"multiple-object-tracking","task_name":"Multiple Object Tracking"},{"task_slug":"object-tracking","task_name":"Object Tracking"}],"methods":[{"method_slug":"test","method_name":"Test"}],"datasets_introduced":[{"slug":"cfc","name":"CFC","full_name":"Caltech Fish Counting Dataset"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2207.09295","atlas_url":"https://app.syntology.ai/?focus=2207.09295","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.09295"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/visipedia/caltech-fish-counting","reach":null}],"summary":{"ran_honours":1,"ran_violates":2},"by_repo_kind":{"official":{"samples":3,"ran":3,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":3,"samples":[{"code_sha256_prefix":"a464a8b991ece624","entry":"get_frame_idx","repo":"visipedia/caltech-fish-counting","repo_kind":"official","path":"CFC/convert.py","file_url":"https://github.com/visipedia/caltech-fish-counting/blob/HEAD/CFC/convert.py","link_basis":"first_harvest_node","language":"python","status":"ran_honours","verification_level":1,"contract_check":"HONOURS","metamorphic_tier":"well_formed","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"a464a8b991ece624"}},{"code_sha256_prefix":"4f472f08805f094b","entry":"has_subdirectories","repo":"visipedia/caltech-fish-counting","repo_kind":"official","path":"CFC/convert.py","file_url":"https://github.com/visipedia/caltech-fish-counting/blob/HEAD/CFC/convert.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"4f472f08805f094b"}},{"code_sha256_prefix":"4d17212862da32e2","entry":"norm","repo":"visipedia/caltech-fish-counting","repo_kind":"official","path":"CFC/evaluate.py","file_url":"https://github.com/visipedia/caltech-fish-counting/blob/HEAD/CFC/evaluate.py","link_basis":"first_harvest_node","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"4d17212862da32e2"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}