Oct 23, 2023 · Abstract:In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view this ...
Wonder3D++ first generates consistent multi-view normal maps with corresponding color images via a cross-domain diffusion model and then leverages a cascaded 3D ...
[PDF] Wonder3D: Single Image to 3D using Cross-Domain Diffusion
openaccess.thecvf.com › papers › L...
Wonder3D reconstructs highly-detailed textured meshes from a single-view image in only 2 ∼ 3 minutes. Wonder3D first generates consistent multi-view normal maps ...
To compare the two geometry representations, we ad- ditionally train Wonder3D using depth instead of normals. The accompanying Figure 8 illustrates the ...
Wonder3D first generates consistent multi-view normal maps with corresponding color images via a cross-domain diffusion model, and then leverages a novel normal ...
In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from single-view images.
View recent discussion. Abstract: In this work, we introduce Wonder3D, a novel method for efficiently generating high-fidelity textured meshes from ...
Wonder3D first generates consistent multi-view normal maps with corresponding color images via a cross-domain diffusion model, and then leverages a novel normal ...
Wonder3D is introduced, a novel method for efficiently generating high-fidelity textured meshes from single-view images using a cross-domain diffusion model ...
Jan 1, 2025 · As a result, it allows for fast convergence and robust generalization, without requiring substantial changes to the stable diffusion models.