Didrpg2emtl_comp.rar May 2026

The network focuses on learning the "rain residual" (the difference between the rainy image and the clean background), making the training process more stable and effective. Content of the .rar File

Instead of attempting to remove all rain in a single step, the model decomposes the rain layer into multiple stages. It progressively removes rain streaks by grouping them based on their physical characteristics. DIDRPG2EMTL_comp.rar

The paper addresses the challenge of removing rain streaks from single images (de-raining) by introducing a recurrent framework that handles rain streaks of varying densities and shapes. The network focuses on learning the "rain residual"

Code to run the de-rainer on the provided sample "Rain200L" or "Rain200H" datasets. The paper addresses the challenge of removing rain

Settings for hyperparameters and directory paths used during the "comp" (computation/comparison) phase of the research. Performance and Impact