Fusion moves for correlation clustering

Abstract

Correlation clustering, or multicut partitioning, is widely used in image segmentation for partitioning an undirected graph or image with positive and negative edge weights such that the sum of cut edge weights is minimized. Due to its NP-hardness, exact solvers do not scale and approximative solvers often give unsatisfactory results. We investigate… (More)
DOI: 10.1109/CVPR.2015.7298973

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