Truncated max-of-convex models
Truncated convex models (TCM) are a special case of pairwise random fields that have been widely used in computer vision. However, by restricting the order of the potentials to be at most two, they fail to capture useful image statistics. We propose a natural generalization of TCM to high-order rand...
Principais autores: | Pansari, P, Mudigonda, P |
---|---|
Formato: | Conference item |
Publicado em: |
Computer Vision Foundation
2017
|
Registros relacionados
-
Truncated max-of-convex models
por: Mudigonda, P, et al.
Publicado em: (2017) -
Improved moves for truncated convex models
por: Kumar, MP, et al.
Publicado em: (2009) -
Improved moves for truncated convex models
por: Pawan Kumar, M, et al.
Publicado em: (2011) -
Optimal submodular extensions for marginal estimation
por: Pansari, P, et al.
Publicado em: (2018) -
On hyperspaces of max-plus and max-min convex sets
por: Bazylevych Lidiya, et al.
Publicado em: (2017-01-01)