In this paper, we present a new blind and robust 3-D mesh watermarking scheme that makes use of the recently proposed manifold harmonics analysis. The mesh spectrum coefficient am...
Kai Wang, Ming Luo, Adrian G. Bors, Florence Denis
In this paper, based on manifold harmonics, we propose a novel framework for 3D shape similarity comparison and partial matching. First, we propose a novel symmetric meanvalue rep...
Huai-Yu Wu, Hongbin Zha, Tao Luo, Xulei Wang, Song...
This paper proposes a novel algorithm for semisupervised learning. This algorithm learns graph cuts that maximize the margin with respect to the labels induced by the harmonic fun...
Branislav Kveton, Michal Valko, Ali Rahimi, Ling H...
We study nonparametric regression between Riemannian manifolds based on regularized empirical risk minimization. Regularization functionals for mappings between manifolds should re...
We represent a shape representation technique using the eigenfunctions of Laplace-Beltrami operator and compare the performance with the conventional spherical harmonic (SPHARM) r...