{"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/one-step-event-driven-high-speed-autofocus","title":"One-Step Event-Driven High-Speed Autofocus","arxiv_id":"2503.01214","date":"2025-03-03","proceeding":"CVPR 2025 1","authors":["Yuhan Bao","Shaohua Gao","Wenyong Li","Kaiwei Wang"],"abstract":"High-speed autofocus in extreme scenes remains a significant challenge. Traditional methods rely on repeated sampling around the focus position, resulting in ``focus hunting''. Event-driven methods have advanced focusing speed and improved performance in low-light conditions; however, current approaches still require at least one lengthy round of ``focus hunting'', involving the collection of a complete focus stack. We introduce the Event Laplacian Product (ELP) focus detection function, which combines event data with grayscale Laplacian information, redefining focus search as a detection task. This innovation enables the first one-step event-driven autofocus, cutting focusing time by up to two-thirds and reducing focusing error by 24 times on the DAVIS346 dataset and 22 times on the EVK4 dataset. Additionally, we present an autofocus pipeline tailored for event-only cameras, achieving accurate results across a range of challenging motion and lighting conditions. All datasets and code will be made publicly available.","url_abs":"https://arxiv.org/abs/2503.01214v1","url_pdf":"https://arxiv.org/pdf/2503.01214v1.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":[],"tasks":[],"methods":[{"method_slug":"focus","method_name":"Focus"},{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2503.01214","atlas_url":"https://app.syntology.ai/?focus=2503.01214","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2503.01214"}},"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":"deterministic:regex_extraction","url":"https://github.com/YuHanBaozju/ELP","reach":null}],"summary":{"ran_fixture":2},"by_repo_kind":{"found_in_text":{"samples":2,"ran":2,"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":2,"samples":[{"code_sha256_prefix":"7ff52ad917ebb46a","entry":"adaptive_filter","repo":"YuHanBaozju/ELP","repo_kind":"found_in_text","path":"DAVIS_ELP/utils/filter.py","file_url":"https://github.com/YuHanBaozju/ELP/blob/HEAD/DAVIS_ELP/utils/filter.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"7ff52ad917ebb46a"}},{"code_sha256_prefix":"df997f1228d3fbbf","entry":"update_filter_laplacian_product","repo":"YuHanBaozju/ELP","repo_kind":"found_in_text","path":"DAVIS_ELP/utils/filter.py","file_url":"https://github.com/YuHanBaozju/ELP/blob/HEAD/DAVIS_ELP/utils/filter.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"df997f1228d3fbbf"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}