Yes, the multi-view normal generation can be significantly improved by incorporating additional cues such as depth information and silhouette constraints. Depth information can provide critical insights into the spatial relationships between different parts of the mesh, allowing the model to generate more accurate normal maps that reflect the true geometry of the object. By integrating depth cues, the model can better understand the 3D structure, leading to enhanced detail and consistency across different views.
Silhouette constraints can also play a vital role in preserving the global structure of the input mesh. By enforcing silhouette alignment during the normal generation process, the model can ensure that the generated normals adhere closely to the outline of the input mesh, reducing the likelihood of artifacts and inconsistencies. This approach would help maintain the integrity of the original shape while allowing for the addition of intricate details.
Combining these cues with the existing multi-view ControlNet architecture could lead to a more robust generation process, resulting in higher-quality outputs that are both visually appealing and geometrically accurate. This would enhance the overall effectiveness of the method in producing detailed and realistic 3D models.