Higher-order Segmentation via Multicuts
Computer Vision and Image Understanding(2016)
摘要
•We propose a novel and general formulation for hyper-graph correlation clustering.•Any permutation invariant function can be included into a multicut problem.•We provide a comparison of LP and ILP cutting plane methods and rounding procedures for the multicut problem.•Many sparse Potts models can be solved to global optimality very efficient by the proposed method.•The C++ implementations used in this manuscript is freely available online.
更多查看译文
关键词
Segmentation,Discrete optimization,Multicut,Markov random fields,Higher-order graphical models,Polyhedral combinatorics,Partitioning,Correlation clustering,Global optimality,Image labeling
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要