A Comprehensive Survey on Enhancing Computer Vision Model Robustness against Common Corruptions

To improve the robustness of computer vision models against common corruptions, methods such as data augmentation, representation learning, knowledge distillation, and network components are employed. These approaches aim to enhance model generalization and reliability in real-world scenarios.