Video Deraining

Video deraining aims to computationally remove rain streaks and droplets from videos, improving the quality and usability of visual data acquired in rainy conditions. Recent research focuses on developing efficient and robust deep learning models, employing architectures like transformers and state space models to leverage temporal information and handle diverse rain patterns, while also addressing challenges specific to nighttime or low-light scenarios. These advancements are crucial for enhancing the performance of various computer vision applications, such as autonomous driving and video surveillance, which are significantly impacted by adverse weather conditions. The development of large-scale datasets and innovative training strategies, such as knowledge distillation and adaptive learning, are also key areas of progress.