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Graph Matching

83 평가 기록 7 datasets

Graph Matching is the problem of finding correspondences between two sets of vertices while preserving complex relational information among them. Since the graph structure has a strong capacity to represent objects and robustness to severe deformation and outliers, it is frequently adopted to formulate various correspondence problems in the field of computer vision. Theoretically, the Graph Matching problem can be solved by exhaustively searching the entire solution space. However, this approach is infeasible in practice because the solution space expands exponentially as the size of input data increases. For that reason, previous studies have attempted to solve the problem by using various approximation techniques.

<span class="description-source">Source: Consistent Multiple Graph Matching with Multi-layer Random Walks Synchronization </span>

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Dataset기록된 모델 예시MetricPaperCode
URL
matching accuracy: 0.818F1 score: 0.717±0.005
논문 -
COMMON
matching accuracy: 0.9910
논문 코드
CREAM
matching accuracy: 0.851
논문 코드
GCAN-AFAT-U
F1 score: 0.715
논문 코드
GCAN-AFAT-I
F1 score: 0.729
논문 코드
Smatch
Spearman Correlation: 96.57
논문 코드
CUB
URL
F1 score: 0.951
논문 -

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