Before revision:  In this work, we address the problem of inpainting on surfaces through a new method based on dictionary learning and sparse coding. Our method learns the dictionary through the subdivision of the mesh into patches and rebuilds the mesh via a method of reconstruction inspired by the Non-local Means method on the computed sparse codes. One of the advantages of our method is that it is capable of filling the missing regions and simultaneously removes noise and enhances important features of the mesh.
After revision:  In this work, we address the problem of sparsely representing discrete surfaces and propose a new representation that is capable of filling the missing regions and simultaneously removes noise and enhances important features of the mesh.