Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
6-2025
Abstract
This paper presents an overview of NTIRE 2025, the First Challenge on Event-Based Image Deblurring, detailing the proposed methodologies and corresponding results. The primary goal of the challenge is to design an event-based method that achieves high-quality image deblurring, with performance quantitatively assessed using Peak Signal-toNoise Ratio (PSNR). Notably, there are no restrictions on computational complexity or model size. The task focuses on leveraging both events and images as inputs for singleimage deblurring. A total of 199 participants registered, among whom 15 teams successfully submitted valid results, offering valuable insights into the current state of eventbased image deblurring. We anticipate that this challenge will drive further advancements in event-based vision research.
Discipline
Software Engineering
Research Areas
Data Science and Engineering
Areas of Excellence
Digital transformation
Publication
Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, Tennessee, USA, June 11-15
First Page
1324
Last Page
1341
ISBN
9798331599959
Identifier
10.1109/CVPRW67362.2025.00124
Publisher
IEEE
City or Country
Pistacataway
Citation
SUN, Lei and et. al..
NTIRE 2025 challenge on event-based image deblurring: Methods and results. (2025). Proceedings of the 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, Tennessee, USA, June 11-15. 1324-1341.
Available at: https://ink.library.smu.edu.sg/sis_research/10741
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/CVPRW67362.2025.00124