Wonder3D presents a cross-domain diffusion model that enhances single-view 3D reconstruction, effectively generating multi-view images and textured meshes with improved quality and consistency.
By leveraging a multiview cross-domain attention mechanism, our method facilitates the exchange of information between views and modalities, which is crucial for achieving coherent and high-quality surface representations.
Our extensive evaluations indicate that Wonder3D not only provides remarkable reconstruction results compared to traditional methods, but also promotes robust generalization and operational efficiency in 3D generation tasks.
The introduction of a geometry-aware normal fusion algorithm allows us to extract high-quality surfaces from multi-view 2D representations, which is essential for producing detailed and accurate 3D models.
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