Developing and integrating advanced image sensors with novel algorithms in camera systems are prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack 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). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Under-Display Camera (UDC) Image Restoration track on MIPI 2022. In total, 167 participants were successfully registered, and 19 teams submitted results in the final testing phase. The developed solutions in this challenge achieved state-of-the-art performance on Under-Display Camera Image Restoration. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found at https://github.com/mipi-challenge/MIPI2022.
翻译:由于对计算摄影和移动平台成像的需求日益增加,开发和整合先进的图像传感器和摄像系统的新算法十分普遍;然而,缺乏高质量的研究数据,工业和学术界深入交流观点的机会很少,限制了移动智能摄影和成像(MIPI)的发展。为了弥合这一差距,我们提出了第一个MIPI挑战,包括五个侧重于新图像传感器和成像算法的轨道。在本文件中,我们总结并审查了MIPI 2022 上的低播放相机图像恢复轨道。总共有167名参与者成功登记,19个团队在最后测试阶段提交了结果。这个挑战中制定的解决办法在Display相机图像恢复方面实现了最先进的表现。本文详细说明了在这一挑战中开发的所有模型。可在https://github.com/mipi-challenge/MIPI2022上找到这一挑战的更多细节和与数据集的链接。