Snow Removal

Snow removal from images and LiDAR point clouds is a burgeoning research area aiming to improve the accuracy and reliability of computer vision systems in adverse weather conditions. Current efforts focus on developing efficient deep learning models, including convolutional neural networks (CNNs) and transformers, often incorporating techniques like self-supervised learning and multi-scale feature extraction to address the complex and varied nature of snow degradation. These advancements are crucial for enhancing the performance of autonomous vehicles, robotics, and other applications reliant on accurate scene understanding in snowy environments. The development of lightweight and real-time capable algorithms is a key priority to enable practical deployment.