Adaptively Transforming Graph Matching

  • Fudong Wang
  • Nan Xue
  • Yipeng Zhang
  • Xiang Bai
  • Gui-Song XiaEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11220)


Recently, many graph matching methods that incorporate pairwise constraint and that can be formulated as a quadratic assignment problem (QAP) have been proposed. Although these methods demonstrate promising results for the graph matching problem, they have high complexity in space or time. In this paper, we introduce an adaptively transforming graph matching (ATGM) method from the perspective of functional representation. More precisely, under a transformation formulation, we aim to match two graphs by minimizing the discrepancy between the original graph and the transformed graph. With a linear representation map of the transformation, the pairwise edge attributes of graphs are explicitly represented by unary node attributes, which enables us to reduce the space and time complexity significantly. Due to an efficient Frank-Wolfe method-based optimization strategy, we can handle graphs with hundreds and thousands of nodes within an acceptable amount of time. Meanwhile, because transformation map can preserve graph structures, a domain adaptation-based strategy is proposed to remove the outliers. The experimental results demonstrate that our proposed method outperforms the state-of-the-art graph matching algorithms.


Graph matching Transformation representation Frank-Wolfe method 



This research is supported by projects of National Natural Science Foundation of China (NSFC) under the contracts No.61771350 and No.41501462.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Fudong Wang
    • 1
  • Nan Xue
    • 1
  • Yipeng Zhang
    • 2
  • Xiang Bai
    • 3
  • Gui-Song Xia
    • 1
    Email author
  1. 1.State Key Laboratory LIESMARSWuhan UniversityWuhanChina
  2. 2.School of Computer ScienceWuhan UniversityWuhanChina
  3. 3.EIS, Huazhong University of Science and TechnologyWuhanChina

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