Novel Class Discovery

Novel class discovery (NCD) focuses on identifying new categories within unlabeled data by leveraging knowledge from previously known classes. Current research emphasizes developing robust algorithms and model architectures, such as those based on self-training, knowledge distillation, and prototype learning, to address challenges like imbalanced class distributions and catastrophic forgetting across various data types (images, point clouds, tabular data, graphs). This field is significant because it enables more adaptable and robust machine learning systems capable of handling open-world scenarios where new classes continuously emerge, impacting applications ranging from biomedical concept discovery to object detection in evolving environments.