MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results
The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems. However, the scarcity of high-quality data for research and the rare opportunity for in-depth e...
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Zusammenfassung: | The increasing demand for computational photography and imaging on mobile
platforms has led to the widespread development and integration of advanced
image sensors with novel algorithms in camera systems. However, the scarcity of
high-quality data for research and the rare opportunity for in-depth exchange
of views from industry and academia constrain the development of mobile
intelligent photography and imaging (MIPI). Building on the achievements of the
previous MIPI Workshops held at ECCV 2022 and CVPR 2023, we introduce our third
MIPI challenge including three tracks focusing on novel image sensors and
imaging algorithms. In this paper, we summarize and review the Few-shot RAW
Image Denoising track on MIPI 2024. In total, 165 participants were
successfully registered, and 7 teams submitted results in the final testing
phase. The developed solutions in this challenge achieved state-of-the-art
erformance on Few-shot RAW Image Denoising. More details of this challenge and
the link to the dataset can be found at https://mipichallenge.org/MIPI2024. |
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DOI: | 10.48550/arxiv.2406.07006 |