Synergizing local and global models for matrix approximation
Chao Chen, Hao Zhang, et al.
CIKM 2019
As two fundamental problems, graph cuts and graph matching have been intensively investigated over the decades, resulting in vast literature in these two topics respectively. However the way of jointly applying and solving graph cuts and matching receives few attention. In this paper, we first formalize the problem of simultaneously cutting a graph into two partitions i.e. graph cuts and establishing their correspondence i.e. graph matching. Then we develop an optimization algorithm by updating matching and cutting alternatively, provided with theoretical analysis. The efficacy of our algorithm is verified on both synthetic dataset and real-world images containing similar regions or structures.
Chao Chen, Hao Zhang, et al.
CIKM 2019
Junchi Yan, Chao Zhang, et al.
CVPR 2015
Chao Xue, Junchi Yan, et al.
CVPR 2019
Chuang Gan, Boqing Gong, et al.
CVPR 2018