Semi Supervised Object Detection

Semi-supervised object detection is a technique in the field of computer vision that combines labeled and unlabeled data for training. This method not only reduces the burden of labeling data and improves the training efficiency of high-performance object detectors, but also enhances the performance and generalization capabilities of the detectors by leveraging a large amount of unlabeled data, making it highly valuable for various applications.