This technical report presents our Restormer-Plus approach, which was submitted to the GT-RAIN Challenge (CVPR 2023 UG$^2$+ Track 3). Details regarding the challenge are available at http://cvpr2023.ug2challenge.org/track3.html. Our Restormer-Plus outperformed all other submitted solutions in terms of peak signal-to-noise ratio (PSNR). It consists mainly of four modules: the single image de-raining module, the median filtering module, the weighted averaging module, and the post-processing module. We named the single-image de-raining module Restormer-X, which is built on Restormer and performed on each rainy image. The median filtering module is employed as a median operator for the 300 rainy images associated with each scene. The weighted averaging module combines the median filtering results with that of Restormer-X to alleviate overfitting if we only use Restormer-X. Finally, the post-processing module is used to improve the brightness restoration. Together, these modules render Restormer-Plus to be one state-of-the-art solution to the GT-RAIN Challenge. Our code is available at https://github.com/ZJLAB-AMMI/Restormer-Plus.

翻译：本技术报告介绍我们提交至GT-RAIN挑战赛（CVPR 2023 UG$^2$+赛道3）的Restormer-Plus方法。挑战赛详情可查阅http://cvpr2023.ug2challenge.org/track3.html。我们的Restormer-Plus在峰值信噪比（PSNR）指标上优于所有其他提交方案。该方法主要由四个模块构成：单图像去雨模块、中值滤波模块、加权平均模块及后处理模块。我们将单图像去雨模块命名为Restormer-X，该模块基于Restormer架构，对每幅雨图独立处理。中值滤波模块对每个场景对应的300张雨图执行中值运算。加权平均模块融合中值滤波结果与Restormer-X的输出，以缓解仅使用Restormer-X可能导致的过拟合问题。最后，后处理模块用于优化亮度恢复效果。上述模块共同使Restormer-X成为GT-RAIN挑战赛的先进解决方案之一。我们的代码开源在https://github.com/ZJLAB-AMMI/Restormer-Plus。