MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results
It addresses the problem of high-quality data scarcity for mobile imaging research, providing a benchmark for industry and academia, but is incremental as part of an ongoing challenge series.
The paper summarizes the MIPI 2024 Challenge on Few-shot RAW Image Denoising, where 7 teams submitted solutions that achieved state-of-the-art performance in denoising with limited data.
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.