Semi Supervised Person Bounding Box Detection

Semi-supervised human bounding box detection is a technique in the field of computer vision that aims to improve the accuracy and efficiency of human detection by utilizing a small amount of labeled data and a large amount of unlabeled data. This method combines the advantages of supervised and unsupervised learning, enabling it to enhance the model's generalization ability while reducing annotation costs. In practical applications, this technology is widely used in intelligent surveillance, human-computer interaction, and autonomous driving, among other scenarios, and has significant application value.