Level Set Mesher: Single-image to 3D reconstruction by following the level sets of the signed distance function

We present Level Set Mesher, a single-image to 3D reconstruction strategy to deform an initial spherical triangular mesh into the 3D geometry of a target shape. Level Set Mesher offsets each vertex in a discrete number of steps following a learned velocity vector field V modeled as a Graph Attention Network. At each step k, we constrain the deformed vertices to lie on the l
k
level set of the target shape’s signed distance function to guide the deformation process. We show that our approach accurately estimates the surface’s normal of the predicted shapes and reduces mesh’s artifacts in the final prediction. We compare our approach with state-of-the-art single-image to 3D reconstruction methods and show improvements in accuracy predictions, resulting in better quality and manifold meshes.