{"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/lc-mamba-local-and-continuous-mamba-with","title":"LC-Mamba: Local and Continuous Mamba with Shifted Windows for Frame Interpolation","arxiv_id":null,"date":"2025-01-01","proceeding":"CVPR 2025 1","authors":["Min Wu Jeong","Chae Eun Rhee"],"abstract":"    In this paper, we propose LC-Mamba, a Mamba-based model that captures fine-grained spatiotemporal information in video frames, addressing limitations in current interpolation methods and enhancing performance. The main contributions are as follows: First, we apply a shifted local window technique to reduce historical decay and enhance local spatial features, allowing multiscale capture of detailed motion between frames. Second, we introduce a Hilbert curve-based selective state scan to maintain continuity across window boundaries, preserving spatial correlations both within and between windows. Third, we extend the Hilbert curve to enable voxel-level scanning to effectively capture spatiotemporal characteristics between frames. The proposed LC-Mamba achieves competitive results, with a PSNR of 36.53 dB on Vimeo-90k, outperforming prior models by +0.03 dB. The code and models are publicly available at https://github.com/Miinuuu/LC-Mamba.git    ","url_abs":"http://openaccess.thecvf.com//content/CVPR2025/html/Jeong_LC-Mamba_Local_and_Continuous_Mamba_with_Shifted_Windows_for_Frame_CVPR_2025_paper.html","url_pdf":"http://openaccess.thecvf.com//content/CVPR2025/papers/Jeong_LC-Mamba_Local_and_Continuous_Mamba_with_Shifted_Windows_for_Frame_CVPR_2025_paper.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":"lc-mamba-local-and-continuous-mamba-with","repo_url":"https://github.com/miinuuu/lc-mamba","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"mamba","task_name":"Mamba"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}