April 2, 2024, 7:47 p.m. | Duosheng Chen, Shihao Zhou, Jinshan Pan, Jinglei Shi, Lishen Qu, Jufeng Yang

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.00358v1 Announce Type: new
Abstract: Exploring motion information is important for the motion deblurring task. Recent the window-based transformer approaches have achieved decent performance in image deblurring. Note that the motion causing blurry results is usually composed of translation and rotation movements and the window-shift operation in the Cartesian coordinate system by the window-based transformer approaches only directly explores translation motion in orthogonal directions. Thus, these methods have the limitation of modeling the rotation part. To alleviate this problem, we …

abstract arxiv cs.cv image information movements performance results rotation shift transformer translation type

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Senior Software Engineer, Generative AI (C++)

@ SoundHound Inc. | Toronto, Canada