SHMT is a self-supervised hierarchical makeup transfer technology achieved through latent diffusion models. This technology allows for the natural transfer of one facial makeup to another without the need for explicit labeling. Its main advantages include the ability to handle complex facial features and expression changes, providing high-quality transfer results. This technology has been accepted at NeurIPS 2024, showcasing its innovation and practicality in the field of image processing.