SoftTeacher is an end-to-end semi-supervised object detection framework that jointly trains a student detector and a teacher model. The teacher generates soft pseudo-labels for unlabeled images, which the student uses for training. This approach improves detection accuracy by utilizing unlabeled data alongside labeled data without requiring additional annotation costs.