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We analyzed the self-occlusion problem that occurs in S3DMM-based 3D face reconstruction and proposed a method for solving this problem.
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In Methods, we formulate the xor-haplotype inference as a sparse dictionary selection problem and present an efficient greedy method for solving this problem.
This compares very favorably with the execution times of other methods used for solving this problem.
The simulated annealing method is adopted for solving this problem.
Informally speaking, a problem \(X\) is said to be reducible to another problem \(Y\) just in case a method for solving \(Y\) would also yield a method for solving \(X\).
Here, we describe a method that solves this problem.
Hence, there is a need for global optimization methods capable of solving this problem efficiently.
Some dynamic and incremental methods are opted for solving this calibration problem for estimating the correct length of segments.
To fit parameters to measured data a numerical method for solving an optimization problem is required.
Select an appropriate method for solving the problem.
This paper develops a novel method for solving such problems.
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