The method presented in the paper can be extended to handle more complex geometric details by integrating advanced texture synthesis techniques and enhancing the multi-view generation process. One approach is to incorporate high-resolution texture maps alongside the normal images generated during the multi-view normal generation stage. By utilizing texture synthesis models that leverage deep learning, the system can generate fine-grained textures that correspond to the intricate surface features of the 3D mesh. Additionally, employing techniques such as texture transfer from high-quality reference images can enrich the output with realistic surface details.
Moreover, the refinement stage could be enhanced by implementing a multi-scale approach, where different levels of detail are processed separately. This would allow the method to focus on generating intricate surface features at a finer scale while maintaining the overall structure of the mesh. Techniques such as procedural texture generation or the use of generative adversarial networks (GANs) could also be explored to create more complex surface patterns and textures, thereby improving the visual fidelity of the final output.