Semi-Supervised Segmentation

Semi-supervised segmentation improves efficiency in tasks where annotation is costly. A small amount of strongly labeled data is combined with a large pool of unlabeled images. Consistency training, pseudo-labeling, and teacher-student frameworks are common in this area. It is one of the key strategies for scalability in expensive supervised segmentation tasks.