{"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/gerd-geometric-event-response-data-generation","title":"GERD: Geometric event response data generation","arxiv_id":"2412.03259","date":"2024-12-04","proceeding":null,"authors":["Jens Egholm Pedersen","Dimitris Korakovounis","Jörg Conradt"],"abstract":"Event-based vision sensors are appealing because of their time resolution, higher dynamic range, and low-power consumption. They also provide data that is fundamentally different from conventional frame-based cameras: events are sparse, discrete, and require integration in time. Unlike conventional models grounded in established geometric and physical principles, event-based models lack comparable foundations. We introduce a method to generate event-based data under controlled transformations. Specifically, we subject a prototypical object to transformations that change over time to produce carefully curated event videos. We hope this work simplifies studies for geometric approaches in event-based vision. GERD is available at https://github.com/ncskth/gerd","url_abs":"https://arxiv.org/abs/2412.03259v1","url_pdf":"https://arxiv.org/pdf/2412.03259v1.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":"gerd-geometric-event-response-data-generation","repo_url":"https://github.com/ncskth/gerd","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"event-based-vision","task_name":"Event-based vision"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}