Semi Supervised Person Instance Segmentation

Semi-supervised person instance segmentation is a technique in the field of computer vision aimed at accurately segmenting individuals in images using a small amount of labeled data and a large amount of unlabeled data. This method enhances the model's generalization ability and segmentation accuracy by leveraging the strengths of both supervised and unsupervised learning, effectively reducing annotation costs and improving the flexibility and practicality of application scenarios. It holds significant application value in areas such as surveillance, human-computer interaction, and virtual reality.