MeshUDF: Fast and Differentiable Meshing of Unsigned Distance Field Networks
This enables more efficient and precise 3D surface reconstruction from non-watertight data, particularly for fitting sparse data with pretrained networks.
The paper tackles the problem of converting Unsigned Distance Fields (UDFs) into explicit meshes, which is often slow or inaccurate, by extending the marching cube algorithm to achieve fast and accurate meshing while also making the process differentiable.
Unsigned Distance Fields (UDFs) can be used to represent non-watertight surfaces. However, current approaches to converting them into explicit meshes tend to either be expensive or to degrade the accuracy. Here, we extend the marching cube algorithm to handle UDFs, both fast and accurately. Moreover, our approach to surface extraction is differentiable, which is key to using pretrained UDF networks to fit sparse data.