2 citations · 2 across the 6 of their papers we have counts for
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Variational Image Motion Estimation by Accelerated Dual Optimization
Hongpeng Sun, Xue-Cheng Tai, Jing Yuan
Estimating optical flows is one of the most interesting problems in computer vision, which estimates the essential information about pixel-wise displacements between two consecutiv…
An Efficient Augmented Lagrangian Method with Semismooth Newton Solver for Total Generalized Variation
Hongpeng Sun
Total generalization variation (TGV) is a very powerful and important regularization for various inverse problems and computer vision tasks. In this paper, we proposed a semismooth…
Efficient ADMM and Splitting Methods for Continuous Min-cut and Max-flow Problems
Hongpeng Sun, Xuecheng Tai, Jing Yuan
The Potts model has many applications. It is equivalent to some min-cut and max-flow models. Primal-dual algorithms have been used to solve these problems. Due to the special struc…
Dualization and Automatic Distributed Parameter Selection of Total Generalized Variation via Bilevel Optimization
Michael Hintermüller, Kostas Papafitsoros, Carlos N. Rautenberg +1
Total Generalized Variation (TGV) regularization in image reconstruction relies on an infimal convolution type combination of generalized first- and second-order derivatives. This…
A Preconditioned Difference of Convex Algorithm for Truncated Quadratic Regularization with Application to Imaging
Shengxiang Deng, Hongpeng Sun
We consider the minimization problem with the truncated quadratic regularization with gradient operator, which is a nonsmooth and nonconvex problem. We cooperated the classical pre…