AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
By: George Ciubotariu , Florin-Alexandru Vasluianu , Zhuyun Zhou and more
Potential Business Impact:
Cleans up blurry pictures from fast movement.
This paper presents a comprehensive review of the AIM 2025 High FPS Non-Uniform Motion Deblurring Challenge, highlighting the proposed solutions and final results. The objective of this challenge is to identify effective networks capable of producing clearer and visually compelling images in diverse and challenging conditions, by learning representative visual cues for complex aggregations of motion types. A total of 68 participants registered for the competition, and 9 teams ultimately submitted valid entries. This paper thoroughly evaluates the state-of-the-art advances in high-FPS single image motion deblurring, showcasing the significant progress in the field, while leveraging samples of the novel dataset, MIORe, that introduces challenging examples of movement patterns.
Similar Papers
Efficient Real-World Deblurring using Single Images: AIM 2025 Challenge Report
CV and Pattern Recognition
Makes blurry photos clear with less computer power.
AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Results
CV and Pattern Recognition
Cleans up dark, grainy videos from phones.
AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Results
CV and Pattern Recognition
Makes normal pictures look like super bright, colorful ones.