BiCoS: A Bi-level co-segmentation method for image classification
Yuning Chai, Victor Lempitsky, Andrew Zisserman · 2011
The objective of this paper is the unsupervised segmentation of image training sets into foreground and background in order to improve image classification performance. To this end we introduce a new scalable, alternation-based algorithm for co-segmentation, BiCoS, which is simpler than many of its predecessors, and yet has superior performance on standard benchmark image datasets.