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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–250 of 477 papers

TitleStatusHype
A Graph-Matching Approach for Cross-view Registration of Over-view 2 and Street-view based Point Clouds—0
A Graph Matching Perspective With Transformers on Video Instance Segmentation—0
AMALGAM: A Matching Approach to fairfy tabuLar data with knowledGe grAph Model—0
A Matrix Decomposition Perspective to Multiple Graph Matching—0
An approach based on Open Research Knowledge Graph for Knowledge Acquisition from scientific papers—0
An Approach to Inference-Driven Dialogue Management within a Social Chatbot—0
An Integer Projected Fixed Point Method for Graph Matching and MAP Inference—0
An Upper Bound for Minimum True Matches in Graph Isomorphism with Simulated Annealing—0
A polynomial time iterative algorithm for matching Gaussian matrices with non-vanishing correlation—0
A polynomial-time iterative algorithm for random graph matching with non-vanishing correlation—0
Applying graph matching techniques to enhance reuse of plant design information—0
An Equity-Aware Recommender System for Curating Art Exhibits Based on Locally-Constrained Graph Matching—0
Articulated Shape Matching Using Laplacian Eigenfunctions and Unsupervised Point Registration—0
A Simple Baseline for Weakly-Supervised Scene Graph Generation—0
Asynchronous Modeling: A Dual-phase Perspective for Long-Tailed Recognition—0
A Systematic Approach for Cross-source Point Cloud Registration by Preserving Macro and Micro Structures—0
Attributed Graph Mining and Matching: An Attempt to Define and Extract Soft Attributed Patterns—0
A Unified Framework for Integer Programming Formulation of Graph Matching Problems—0
AutoShuffleNet: Learning Permutation Matrices via an Exact Lipschitz Continuous Penalty in Deep Convolutional Neural Networks—0
A Weighted Common Subgraph Matching Algorithm—0
Bigraph Matching Weighted with Learnt Incentive Function for Multi-Robot Task Allocation—0
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport—0
Bilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport—0
Binary Constraint Preserving Graph Matching—0
Bipartite Graph Matching for Keyframe Summary Evaluation—0
Bi-VLGM : Bi-Level Class-Severity-Aware Vision-Language Graph Matching for Text Guided Medical Image Segmentation—0
Blind Graph Matching Using Graph Signals—0
BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDAR—0
Bridge the Gap Between Visual and Linguistic Comprehension for Generalized Zero-shot Semantic Segmentation—0
Category-level 6D Object Pose Recovery in Depth Images—0
CIGAR: Cross-Modality Graph Reasoning for Domain Adaptive Object Detection—0
CLIP-Clique: Graph-based Correspondence Matching Augmented by Vision Language Models for Object-based Global Localization—0
Clique-Graph Matching by Preserving Global & Local Structure—0
Closing the Loop: Graph Networks to Unify Semantic Objects and Visual Features for Multi-object Scenes—0
Clustered Graph Matching for Label Recovery and Graph Classification—0
Differentiable Combinatorial Losses through Generalized Gradients of Linear Programs—0
Complex Ontology Matching with Large Language Model Embeddings—0
Computing Optimal Assignments in Linear Time for Approximate Graph Matching—0
Exploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification—0
Consistent Multiple Graph Matching with Multi-layer Random Walks Synchronization—0
Consistent polynomial-time unseeded graph matching for Lipschitz graphons—0
Contactless Fingerprint Recognition Using 3D Graph Matching—0
ContrastAlign: Toward Robust BEV Feature Alignment via Contrastive Learning for Multi-Modal 3D Object Detection—0
Contrastive General Graph Matching with Adaptive Augmentation Sampling—0
Convex Joint Graph Matching and Clustering via Semidefinite Relaxations—0
Convex Two-Layer Modeling with Latent Structure—0
Coronary Artery Semantic Labeling using Edge Attention Graph Matching Network—0
Correlated Stochastic Block Models: Exact Graph Matching with Applications to Recovering Communities—0
CPN-CORE: A Text Semantic Similarity System Infused with Opinion Knowledge—0
Cross-domain Named Entity Recognition via Graph Matching—0
Show:102550
← PrevPage 5 of 10Next →
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