AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
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Abstract (arXiv)
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.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 16 of its 36 references that are in the map. First posted on arXiv 8 Sep 2025.
Builds on
16 of 36 references.
References · 16
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4 more
- 2025AIM 2025 Low-light RAW Video Denoising Challenge: Dataset, Methods and Resultscited by 14
- 2025AIM 2025 challenge on Inverse Tone Mapping Report: Methods and Resultscited by 8
- 2025AIM 2025 Rip Current Segmentation (RipSeg) Challenge Reportcited by 7
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Citing papers per year: 2025: 2.
2 papers.