{"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/joint-filtering-of-intensity-images-and","title":"Joint Filtering of Intensity Images and Neuromorphic Events for High-Resolution Noise-Robust Imaging","arxiv_id":null,"date":"2020-06-01","proceeding":"CVPR 2020 6","authors":["Zihao W. Wang"," Peiqi Duan"," Oliver Cossairt"," Aggelos Katsaggelos"," Tiejun Huang"," Boxin Shi"],"abstract":"We present a novel computational imaging system with high resolution and low noise. Our system consists of a traditional video camera which captures high-resolution intensity images, and an event camera which encodes high-speed motion as a stream of asynchronous binary events. To process the hybrid input, we propose a unifying framework that first bridges the two sensing modalities via a noise-robust motion compensation model, and then performs joint image filtering. The filtered output represents the temporal gradient of the captured space-time volume, which can be viewed as motion-compensated event frames with high resolution and low noise. Therefore, the output can be widely applied to many existing event-based algorithms that are highly dependent on spatial resolution and noise robustness. In experimental results performed on both publicly available datasets as well as our contributing RGB-DAVIS dataset, we show systematic performance improvement in applications such as high frame-rate video synthesis, feature/corner detection and tracking, as well as high dynamic range image reconstruction.\r","url_abs":"http://openaccess.thecvf.com/content_CVPR_2020/html/Wang_Joint_Filtering_of_Intensity_Images_and_Neuromorphic_Events_for_High-Resolution_CVPR_2020_paper.html","url_pdf":"http://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_Joint_Filtering_of_Intensity_Images_and_Neuromorphic_Events_for_High-Resolution_CVPR_2020_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":[],"tasks":[{"task_slug":"image-reconstruction","task_name":"Image Reconstruction"},{"task_slug":"motion-compensation","task_name":"Motion Compensation"}],"methods":[],"datasets_introduced":[{"slug":"rgb-davis-dataset","name":"RGB-DAVIS Dataset","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}