Restormer-Plus for Real World Image Deraining: One State-of-the-Art Solution to the GT-RAIN Challenge (CVPR 2023 UG$^2$+ Track 3)

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.