MIPI 2024 Challenge on Nighttime Flare Removal: Methods and Results
Yuekun Dai, Dafeng Zhang, Xiaoming Li, Zongsheng Yue, Chongyi Li,, Shangchen Zhou, Ruicheng Feng, Peiqing Yang, Zhezhu Jin, Guanqun Liu, Chen, Change Loy, Lize Zhang, Shuai Liu, Chaoyu Feng, Luyang Wang, Shuan Chen,, Guangqi Shao, Xiaotao Wang, Lei Lei, Qirui Yang, Qihua Cheng

TL;DR
The MIPI 2024 challenge on Nighttime Flare Removal brought together 170 participants to develop and evaluate advanced imaging algorithms, achieving state-of-the-art results in nighttime flare removal for mobile photography.
Contribution
This paper presents the third MIPI challenge focusing on nighttime flare removal, including a new dataset and benchmarking results from 14 participating teams.
Findings
Achieved state-of-the-art performance in flare removal
14 teams submitted results, demonstrating active research community
The challenge dataset is publicly available for future research
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 Nighttime Flare Removal track on MIPI 2024. In total, 170 participants were successfully registered, and 14 teams submitted results in the final testing phase. The developed solutions in this challenge achieved…
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Taxonomy
TopicsOil, Gas, and Environmental Issues
