RodinHD is a high-fidelity 3D avatar generation technology based on diffusion models, developed by researchers including Bowen Zhang and Yiji Cheng. It aims to generate detailed 3D avatars from a single portrait image. This technology addresses the shortcomings of existing methods in capturing complex details such as hairstyles by employing novel data scheduling strategies and weight integration regularization terms, improving the decoder's ability to render sharp details. Additionally, it optimizes the guiding effect of portrait images through multi-scale feature representation and cross-attention mechanisms, resulting in 3D avatars with significantly enhanced detail compared to previous methods. Notably, it also exhibits strong generalization capabilities to wild portrait inputs.