Continual Semantic Segmentation

Continual Semantic Segmentation is a sub-task in the field of computer vision that aims to enable models to continuously learn and adapt to new categories and environments without forgetting previously learned knowledge. This task achieves effective processing of new data by continuously updating model parameters, while maintaining recognition capabilities for old data, thereby enhancing the model's generalization ability and long-term stability. Its application value lies in real-time image analysis and understanding in dynamic environments, such as autonomous driving and intelligent surveillance scenarios.