text-to-pose is a research project aimed at generating character poses from text descriptions and using these poses to create images. This technology combines natural language processing and computer vision, achieving text-to-image generation by enhancing the control and quality of diffusion models. The project is based on a paper published at the NeurIPS 2024 Workshop, showcasing innovation and cutting-edge advancements. The key advantages of this technology include improved accuracy and controllability in image generation, as well as potential applications in artistic creation and virtual reality.