{"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/cesped-a-new-benchmark-for-supervised","title":"CESPED: a new benchmark for supervised particle pose estimation in Cryo-EM","arxiv_id":"2311.06194","date":"2023-11-10","proceeding":null,"authors":["Ruben Sanchez-Garcia","Michael Saur","Javier Vargas","Carl Poelking","Charlotte M Deane"],"abstract":"Cryo-EM is a powerful tool for understanding macromolecular structures, yet current methods for structure reconstruction are slow and computationally demanding. To accelerate research on pose estimation, we present CESPED, a new dataset specifically designed for Supervised Pose Estimation in Cryo-EM. Alongside CESPED, we provide a PyTorch package to simplify Cryo-EM data handling and model evaluation. We evaluated the performance of a baseline model, Image2Sphere, on CESPED, which showed promising results but also highlighted the need for further improvements. Additionally, we illustrate the potential of deep learning-based pose estimators to generalise across different samples, suggesting a promising path toward more efficient processing strategies. CESPED is available at https://github.com/oxpig/cesped.","url_abs":"https://arxiv.org/abs/2311.06194v5","url_pdf":"https://arxiv.org/pdf/2311.06194v5.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":"cesped-a-new-benchmark-for-supervised","repo_url":"https://github.com/oxpig/cesped","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"cesped-a-new-benchmark-for-supervised","repo_url":"https://github.com/rsanchezgarc/cesped","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"pose-estimation","task_name":"Pose Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}