Rain Removal

Rain removal, the process of digitally restoring images and videos obscured by rain, aims to improve visibility and enhance the reliability of computer vision systems. Current research focuses on developing advanced deep learning models, including transformers and convolutional neural networks, often incorporating multi-scale architectures and attention mechanisms to effectively remove rain streaks, raindrops, and haze, sometimes leveraging light field data or dual-pixel sensors for improved accuracy. These advancements are significant for various applications, such as autonomous driving, remote sensing, and enhancing the performance of other computer vision tasks that rely on clear imagery. The development of larger, more diverse datasets, particularly those encompassing nighttime and raindrop-focused scenarios, is also a key area of ongoing work.