  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.
