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

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Showing 251–300 of 477 papers

TitleStatusHype
Sparse Quadratic Optimisation over the Stiefel Manifold with Application to Permutation Synchronisation—0
One-shot Key Information Extraction from Document with Deep Partial Graph Matching—0
An Analysis of Euclidean vs. Graph-Based Framing for Bilingual Lexicon Induction from Word Embedding SpacesCode0
Matching with Transformers in MELT—0
Joint Graph Learning and Matching for Semantic Feature CorrespondenceCode0
Weisfeiler-Leman in the BAMBOO: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity—0
Adaptive Edge Attention for Graph Matching with OutliersCode0
Deep graph matching meets mixed-integer linear programming: Relax at your own risk ?Code0
Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities—0
Adiabatic Quantum Graph Matching with Permutation Matrix Constraints—0
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching—0
Multi-Modal Relational Graph for Cross-Modal Video Moment Retrieval—0
G2DA: Geometry-Guided Dual-Alignment Learning for RGB-Infrared Person Re-Identification—0
Stochastic Iterative Graph MatchingCode0
IA-GM: A Deep Bidirectional Learning Method for Graph Matching—0
Pairwise Point Cloud Registration using Graph Matching and Rotation-invariant Features—0
VersaGNN: a Versatile accelerator for Graph neural networks—0
GM-MLIC: Graph Matching based Multi-Label Image Classification—0
Hierarchical Adaptive Pooling by Capturing High-order Dependency for Graph Representation Learning—0
Integrating 2D and 3D Digital Plant Information Towards Automatic Generation of Digital Twins—0
Permutation-Invariant Subgraph DiscoveryCode0
Graph Matching and Graph Rewriting: GREW tools for corpus exploration, maintenance and conversion—0
Joint Deep Multi-Graph Matching and 3D Geometry Learning from Inhomogeneous 2D Image Collections—0
Probabilistic Analogical Mapping with Semantic Relation Networks—0
Applying graph matching techniques to enhance reuse of plant design information—0
The Power of D-hops in Matching Power-Law Graphs—0
MultiTalk: A Highly-Branching Dialog Testbed for Diverse Conversations—0
Settling the Sharp Reconstruction Thresholds of Random Graph Matching—0
Fusion Moves for Graph MatchingCode0
Random Graph Matching with Improved Noise Robustness—0
Knowledge Generation -- Variational Bayes on Knowledge GraphsCode0
AMALGAM: A Matching Approach to fairfy tabuLar data with knowledGe grAph Model—0
Learning to Search for Fast Maximum Common Subgraph Detection—0
Learning Latent Topology for Graph Matching—0
Hypergraph Neural Networks for Hypergraph MatchingCode0
Asynchronous Modeling: A Dual-phase Perspective for Long-Tailed Recognition—0
A Simple Baseline for Weakly-Supervised Scene Graph Generation—0
Occluded Person Re-Identification With Single-Scale Global Representations—0
Multi-level Graph Matching Networks for Deep and Robust Graph Similarity Learning—0
Some Algorithms on Exact, Approximate and Error-Tolerant Graph Matching—0
Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration—0
Partial Gromov-Wasserstein Learning for Partial Graph Matching—0
Cross-modal registration using point clouds and graph-matching in the context of correlative microscopiesCode0
Adversarial Attacks on Deep Graph Matching—0
Graduated Assignment for Joint Multi-Graph Matching and Clustering with Application to Unsupervised Graph Matching Network LearningCode0
Dominant Z-Eigenpairs of Tensor Kronecker Products are Decoupled and Applications to Higher-Order Graph Matching—0
Deep Graph Matching and Searching for Semantic Code Retrieval—0
High-Order Relation Construction and Mining for Graph Matching—0
A general approach for identifying hierarchical symmetry constraints for analog circuit layout—0
Graph Edit Distance Reward: Learning to Edit Scene Graph—0
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All datasetsPASCAL VOCWillow Object ClassSPair-71kIMCPT-SparseGM-100IMCPT-SparseGM-50RARECUB

Benchmark Results

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