Generalized Few Shot Semantic Segmentation

Generalized Few-Shot Semantic Segmentation is a cutting-edge technique in computer vision aimed at achieving efficient pixel-level classification of new categories with only a few annotated samples. This method not only enhances the model's generalization capability but also significantly reduces the cost of data annotation, making it highly applicable to scenarios such as medical image analysis and autonomous driving, where it holds significant practical value.