Research on Simplified Mesh Deformation Based on Differentiable Computation

In this paper, we propose a simplified mesh deformation method based on the differentiable calculation and uses the Pytorch3D library of deep learning. There are four stages, simplification, deformation, subdivision, re-deformation in this method. The simplification stage transforms the original target mesh into a simple mesh. The deformation stage uses the Pytorch3D tool to predict the simple mesh in the simplification result. The subdivision stage subdivides the resulting mesh of deformation, and the re-deformation stage uses the subdivision stage result mesh as the source mesh to predict the original target mesh. Our experiment shows that the number of iterations is similar or less in terms of shape and local features after simplifying the predicted target mesh. Our method is superior to the direct mesh deformation method in terms of mesh deformation speed and local mesh characteristics of deformation and has a better deformation effect.