9.2k citations · 11k across the 18 of their papers we have counts for
7 papers · 1 filter
Higher-order MRFs based image super resolution: why not MAP?
Yunjin Chen
A trainable filter-based higher-order Markov Random Fields (MRFs) model - the so called Fields of Experts (FoE), has proved a highly effective image prior model for many classic im…
iPiano: Inertial Proximal Algorithm for Non-Convex Optimization
Peter Ochs, Yunjin Chen, Thomas Brox +1
In this paper we study an algorithm for solving a minimization problem composed of a differentiable (possibly non-convex) and a convex (possibly non-differentiable) function. The a…
A higher-order MRF based variational model for multiplicative noise reduction
Yunjin Chen, Wensen Feng, René Ranftl +2
The Fields of Experts (FoE) image prior model, a filter-based higher-order Markov Random Fields (MRF) model, has been shown to be effective for many image restoration problems. Mot…
Revisiting loss-specific training of filter-based MRFs for image restoration
Yunjin Chen, Thomas Pock, René Ranftl +1
It is now well known that Markov random fields (MRFs) are particularly effective for modeling image priors in low-level vision. Recent years have seen the emergence of two main app…
Learning -based analysis and synthesis sparsity priors using bi-level optimization
Yunjin Chen, Thomas Pock, Horst Bischof
We consider the analysis operator and synthesis dictionary learning problems based on the the regularized sparse representation model. We reveal the internal relations bet…
Insights into analysis operator learning: From patch-based sparse models to higher-order MRFs
Yunjin Chen, René Ranftl, Thomas Pock
This paper addresses a new learning algorithm for the recently introduced co-sparse analysis model. First, we give new insights into the co-sparse analysis model by establishing co…