{"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/visual-gyroscope-combination-of-deep-learning","title":"Visual Gyroscope: Combination of Deep Learning Features and Direct Alignment for Panoramic Stabilization","arxiv_id":"2402.01461","date":"2024-02-02","proceeding":null,"authors":["Bruno Berenguel-Baeta","Antoine N. Andre","Guillaume Caron","Jesus Bermudez-Cameo","Jose J. Guerrero"],"abstract":"In this article we present a visual gyroscope based on equirectangular panoramas. We propose a new pipeline where we take advantage of combining three different methods to obtain a robust and accurate estimation of the attitude of the camera. We quantitatively and qualitatively validate our method on two image sequences taken with a $360^\\circ$ dual-fisheye camera mounted on different aerial vehicles.","url_abs":"https://arxiv.org/abs/2402.01461v1","url_pdf":"https://arxiv.org/pdf/2402.01461v1.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":"visual-gyroscope-combination-of-deep-learning","repo_url":"https://github.com/sbrunoberenguel/holinet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[],"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}