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. Restormer-Plus outperformed all other submitted solutions in terms of peak signal-to-noise ratio (PSNR), and ranked 4th in terms of structural similarity (SSIM). It was officially evaluated by the competition organizers as a runner-up solution. It consists of four main modules: the single-image de-raining module (Restormer-X), the median filtering module, the weighted averaging module, and the post-processing module. Restormer-X is applied to each rainy image and built on top of Restormer. The median filtering module is used as a median operator for rainy images associated with each scene. The weighted averaging module combines the median filtering results with those of Restormer-X to alleviate overfitting caused by using only Restormer-X. Finally, the post-processing module is utilized to improve the brightness restoration. These modules make Restormer-Plus one of the state-of-the-art solutions for the GT-RAIN Challenge. Our code can be found at https://github.com/ZJLAB-AMMI/Restormer-Plus.

翻译：本技术报告介绍了我们提交至GT-RAIN挑战赛（CVPR 2023 UG²+ Track 3）的Restormer-Plus方法。挑战赛详情可参见http://cvpr2023.ug2challenge.org/track3.html。Restormer-Plus在峰值信噪比（PSNR）指标上超越所有其他提交方案，并在结构相似性（SSIM）指标上排名第四，经竞赛主办方正式评定为亚军方案。该方法包含四个核心模块：单幅图像去雨模块（Restormer-X）、中值滤波模块、加权平均模块和后处理模块。Restormer-X应用于每张雨图，并基于Restormer架构构建；中值滤波模块作为针对每个场景中雨图的中值算子；加权平均模块将中值滤波结果与Restormer-X的输出相融合，以缓解仅使用Restormer-X导致的过拟合问题；后处理模块则用于改善亮度恢复效果。这些模块使Restormer-X成为GT-RAIN挑战赛的最先进解决方案之一。我们的代码可在https://github.com/ZJLAB-AMMI/Restormer-Plus获取。