We adopt Zero123 [31], RealFusion [38], Magic123 [44], One-2-3-45 [30], Point-E [41], Shap-E [25] and a recent work SyncDreamer [33] as baseline methods.

To extract explicit 3D geometry from 2D normal maps and color images, we optimize a neural implicit signed distance field to amalgamate all 2D generated data.

We evaluate the quality of the reconstructed geometry of different methods. The quantitative results are summarized in Table 1.

In this paper, we present Wonder3D, an innovative approach designed for efficiently generating high10 fidelity textured meshes from single-view images.

In this section, we conduct a set of studies to verify the effectiveness of our designs as well as the properties of the method.