Pose Contrastive Learning

Pose Contrastive Learning is a deep learning method in the field of computer vision aimed at extracting key feature representations of human poses through a contrastive learning framework. This method enhances the model's robustness and generalization capability to complex pose variations by maximizing the differences between different samples and minimizing the differences among samples of the same category. Pose Contrastive Learning has demonstrated significant value in applications such as action recognition, behavior analysis, and human-computer interaction, effectively improving the accuracy and stability of systems.