MIPI 2024 Challenge on Few-shot RAW Image Denoising: Methods and Results

TL;DR

This paper summarizes the third MIPI challenge on Few-shot RAW Image Denoising, highlighting the participating teams, their solutions, and the state-of-the-art results achieved in this emerging area of mobile imaging.

Contribution

It introduces the latest challenge framework, reports on participant results, and advances the state-of-the-art in few-shot RAW image denoising techniques.

Findings

7 teams submitted results demonstrating improved denoising performance

State-of-the-art results achieved on the Few-shot RAW Image Denoising task

The challenge fosters collaboration between industry and academia in mobile imaging

Abstract

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.