SOTAVerified

Graph Matching

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.

Source: Consistent Multiple Graph Matching with Multi-layer Random Walks Synchronization

Papers

Showing 426450 of 477 papers

TitleStatusHype
Efficient random graph matching via degree profilesCode0
Learning a Fixed-Length Fingerprint RepresentationCode0
Mind Artist: Creating Artistic Snapshots with Human ThoughtCode0
Deep graph matching meets mixed-integer linear programming: Relax at your own risk ?Code0
Model-based inexact graph matching on top of CNNs for semantic scene understandingCode0
A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial ProblemsCode0
Graph Matching via convex relaxation to the simplexCode0
Cross-modal registration using point clouds and graph-matching in the context of correlative microscopiesCode0
Alternating Direction Graph MatchingCode0
MTab: Matching Tabular Data to Knowledge Graph using Probability ModelsCode0
Muffliato: Peer-to-Peer Privacy Amplification for Decentralized Optimization and AveragingCode0
Template based Graph Neural Network with Optimal Transport DistancesCode0
Multi-Image Semantic Matching by Mining Consistent FeaturesCode0
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural NetworkCode0
Vi-Fi: Associating Moving Subjects across Vision and Wireless SensorsCode0
R-local unlabeled sensing: A novel graph matching approach for multiview unlabeled sensing under local permutationsCode0
Automatic Semantic Modeling for Structural Data Source with the Prior Knowledge from Knowledge BaseCode0
Graph Matching Networks for Learning the Similarity of Graph Structured ObjectsCode0
Learning-based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set MatchingCode0
A Study of Lagrangean Decompositions and Dual Ascent Solvers for Graph MatchingCode0
Graph matching between bipartite and unipartite networks: to collapse, or not to collapse, that is the questionCode0
SMARAGD: Learning SMatch for Accurate and Rapid Approximate Graph DistanceCode0
Rematch: Robust and Efficient Matching of Local Knowledge Graphs to Improve Structural and Semantic SimilarityCode0
Smatch: an Evaluation Metric for Semantic Feature StructuresCode0
Co-attention Graph Pooling for Efficient Pairwise Graph Interaction LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1GMT-BBGMmatching accuracy0.84Unverified
2GMTRmatching accuracy0.84Unverified
3COMMONmatching accuracy0.83Unverified
4GCANmatching accuracy0.82Unverified
5URLmatching accuracy0.82Unverified
6CREAMmatching accuracy0.81Unverified
7ASAR-GMmatching accuracy0.81Unverified
8GAMnetmatching accuracy0.81Unverified
9NHGM-v2matching accuracy0.8Unverified
10EAGMmatching accuracy0.71Unverified
#ModelMetricClaimedVerifiedStatus
1COMMONmatching accuracy0.99Unverified
2GANN-MGMmatching accuracy0.99Unverified
3URLmatching accuracy0.99Unverified
4CREAMmatching accuracy0.99Unverified
5Direct-MGMmatching accuracy0.99Unverified
6GMT-BBGMmatching accuracy0.98Unverified
7Direct-2HGMmatching accuracy0.98Unverified
8qc-DGM2matching accuracy0.98Unverified
9NGM-v2matching accuracy0.98Unverified
10BBGMmatching accuracy0.97Unverified
#ModelMetricClaimedVerifiedStatus
1CREAMmatching accuracy0.85Unverified
2COMMONmatching accuracy0.85Unverified
3GMTRmatching accuracy0.83Unverified
4GMT-BBGMmatching accuracy0.83Unverified
5BBGMmatching accuracy0.82Unverified
6GCANmatching accuracy0.82Unverified
7NGM-v2matching accuracy0.81Unverified
8NGMmatching accuracy0.69Unverified
#ModelMetricClaimedVerifiedStatus
1GCAN-AFAT-UF1 score0.72Unverified
2GCAN-AFAT-IF1 score0.71Unverified
3NGMv2-AFAT-UF1 score0.7Unverified
4NGMv2-AFAT-IF1 score0.7Unverified
5NGMv2F1 score0.68Unverified
6PCA-GMF1 score0.58Unverified
#ModelMetricClaimedVerifiedStatus
1GCAN-AFAT-IF1 score0.73Unverified
2NGMv2-AFAT-IF1 score0.73Unverified
3NGMv2-AFAT-UF1 score0.72Unverified
4GCAN-AFAT-UF1 score0.71Unverified
5NGMv2F1 score0.7Unverified
6PCA-GMF1 score0.63Unverified
#ModelMetricClaimedVerifiedStatus
1SmatchSpearman Correlation96.57Unverified
2RematchSpearman Correlation95.32Unverified
3SemBleuSpearman Correlation94.83Unverified
4S2matchSpearman Correlation94.11Unverified
5WLKSpearman Correlation90.39Unverified
#ModelMetricClaimedVerifiedStatus
1URLF1 score0.95Unverified
2GUMBEL-IPFF1 score0.84Unverified
3IPCA-GMF1 score0.83Unverified
4GANN-MGMF1 score0.83Unverified