Before revision:  Finally, guided normal filtering is performed to obtain filtered face normals, according to which denoised positions of vertices are derived . Compared to the state-of-the-art works, the proposed scheme can generate accurate guidance normals and remove noise effectively while preserving original features and avoiding pseudo-features.
After revision:  Finally, guided normal filtering is performed to obtain filtered face normals, according to which denoised positions of vertices are derived . Compared to the state-of-the-art works, NormalNet can effectively remove noise while preserving the original features and avoiding pseudo-features.