Restormer-Plus for Real World Image Deraining: One State-of-the-Art Solution to the GT-RAIN Challenge (CVPR 2023 UG2+ Track 3)
| Autor: | Zheng, Chaochao, Wang, Luping, Liu, Bin |
|---|---|
| Rok vydání: | 2023 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | 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. Comment: 4 pages |
| Databáze: | arXiv |
| Externí odkaz: |
|