Local Submodularization for Binary Pairwise Energies.
Computer Vision and Pattern Recognition(2017)
摘要
Many computer vision problems require optimization of binary non-submodular energies. We propose a general optimization framework based on local submodular approximations (LSA). Unlike standard LP relaxation methods that linearize the whole energy globally, our approach iteratively approximates the energy locally. On the other hand, unlike standard local optimization methods (e.g., gradient descen...
更多查看译文
关键词
Optimization,Standards,Upper bound,Taylor series,Approximation algorithms,Linear approximation,Computer vision
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要