Existing approaches for diffusion on graphs, e.g., for label propagation, are mainly focused on isotropic diffusion, which is induced by the commonly-used graph Laplacian regularizer. Inspired by the success of diffusivity tensors for anisotropic diffusion in image processing, we presents anisotropic diffusion on graphs and the corresponding label propagation algorithm. We develop positive definite diffusivity operators on the vector bundles of Riemannian manifolds, and discretize them to diffusivity operators on graphs. This enables us to easily define new robust diffusivity operators which significantly improve semi-supervised learning performance over existing diffusion algorithms.
|Title of host publication||Proc. IEEE International Conference on Computer Vision (ICCV), 2015|
|Number of pages||9|
|Publication status||Published - 2015|
|Event||2015 IEEE International Conference on Computer Vision Workshop (ICCVW) - Santiago, Chile|
Duration: 7 Dec 2015 → 13 Dec 2015
|Conference||2015 IEEE International Conference on Computer Vision Workshop (ICCVW)|
|Period||7/12/15 → 13/12/15|