Papers Graph Matching
“Graph Matching” 태그가 달린 논문 515편 · 필터 해제
MTab: Matching Tabular Data to Knowledge Graph using Probability Models
This paper presents the design of our system, namely MTab, for Semantic Web Challenge on Tabular Data to Knowledge Graph Matching (SemTab 2019). MTab combines the voting algorithm and the probability models to solve crit…
Entity TypingGraph MatchingNamed Entity Recognition (NER)Relation Extraction+1Deformable Surface Tracking by Graph Matching
This paper addresses the problem of deformable surface tracking from monocular images. Specifically, we propose a graph-based approach that effectively explores the structure information of the surface to enhance trackin…
Graph MatchingHierarchical Graph Matching Networks for Deep Graph Similarity Learning
While the celebrated graph neural networks yields effective representations for individual nodes of a graph, there has been relatively less success in extending to deep graph similarity learning. Recent work has conside…
Graph MatchingGraph Neural NetworkGraph SimilarityLearning a Fixed-Length Fingerprint Representation
We present DeepPrint, a deep network, which learns to extract fixed-length fingerprint representations of only 200 bytes. DeepPrint incorporates fingerprint domain knowledge, including alignment and minutiae detection, i…
Graph MatchingRe-RankingExploiting Global Camera Network Constraints for Unsupervised Video Person Re-identification
Many unsupervised approaches have been proposed recently for the video-based re-identification problem since annotations of samples across cameras are time-consuming. However, higher-order relationships across the entire…
Graph MatchingMetric LearningPerson Re-IdentificationUnsupervised Person Re-Identification+1IsoNN: Isomorphic Neural Network for Graph Representation Learning and Classification
Deep learning models have achieved huge success in numerous fields, such as computer vision and natural language processing. However, unlike such fields, it is hard to apply traditional deep learning models on the graph …
ClassificationGeneral ClassificationGraph ClassificationGraph Matching+2Spectral Graph Matching and Regularized Quadratic Relaxations II: Erdős-Rényi Graphs and Universality
We analyze a new spectral graph matching algorithm, GRAph Matching by Pairwise eigen-Alignments (GRAMPA), for recovering the latent vertex correspondence between two unlabeled, edge-correlated weighted graphs. Extending …
Graph MatchingSpectral Graph Matching and Regularized Quadratic Relaxations I: The Gaussian Model
Graph matching aims at finding the vertex correspondence between two unlabeled graphs that maximizes the total edge weight correlation. This amounts to solving a computationally intractable quadratic assignment problem. …
Computational EfficiencyGraph MatchingAccurate Congenital Heart Disease Model Generation for 3D Printing
3D printing has been widely adopted for clinical decision making and interventional planning of Congenital heart disease (CHD), while whole heart and great vessel segmentation is the most significant but time-consuming s…
AnatomyDecision MakingGraph MatchingSegmentationSDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration Without Correspondences
This paper presents a novel randomized algorithm for robust point cloud registration without correspondences. Most existing registration approaches require a set of putative correspondences obtained by extracting invaria…
Graph MatchingPoint Cloud RegistrationA Convex Relaxation for Multi-Graph Matching
We present a convex relaxation for the multi-graph matching problem. Our formulation allows for partial pairwise matchings, guarantees cycle consistency, and our objective incorporates both linear and quadratic costs. Mo…
Graph MatchingCross-lingual Knowledge Graph Alignment via Graph Matching Neural Network
Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs. I…
Entity EmbeddingsGraph AttentionGraph MatchingSemBleu: A Robust Metric for AMR Parsing Evaluation
Evaluating AMR parsing accuracy involves comparing pairs of AMR graphs. The major evaluation metric, SMATCH (Cai and Knight, 2013), searches for one-to-one mappings between the nodes of two AMRs with a greedy hill-climbi…
AMR ParsingGraph MatchingSentenceScalable Gromov-Wasserstein Learning for Graph Partitioning and Matching
We propose a scalable Gromov-Wasserstein learning (S-GWL) method and establish a novel and theoretically-supported paradigm for large-scale graph analysis. The proposed method is based on the fact that Gromov-Wasserstein…
ClusteringGraph Matchinggraph partitioningGraph Matching Networks for Learning the Similarity of Graph Structured Objects
This paper addresses the challenging problem of retrieval and matching of graph structured objects, and makes two key contributions. First, we demonstrate how Graph Neural Networks (GNN), which have emerged as an effecti…
Graph AttentionGraph MatchingRetrievalRadar-only ego-motion estimation in difficult settings via graph matching
Radar detects stable, long-range objects under variable weather and lighting conditions, making it a reliable and versatile sensor well suited for ego-motion estimation. In this work, we propose a radar-only odometry pip…
Graph MatchingMotion EstimationDecoding Molecular Graph Embeddings with Reinforcement Learning
We present RL-VAE, a graph-to-graph variational autoencoder that uses reinforcement learning to decode molecular graphs from latent embeddings. Methods have been described previously for graph-to-graph autoencoding, but …
Graph Matchingreinforcement-learningReinforcement LearningReinforcement Learning (RL)Probabilistic Permutation Synchronization using the Riemannian Structure of the Birkhoff Polytope
We present an entirely new geometric and probabilistic approach to synchronization of correspondences across multiple sets of objects or images. In particular, we present two algorithms: (1) Birkhoff-Riemannian L-BFGS fo…
Graph MatchingSOSNet: Second Order Similarity Regularization for Local Descriptor Learning
Despite the fact that Second Order Similarity (SOS) has been used with significant success in tasks such as graph matching and clustering, it has not been exploited for learning local descriptors. In this work, we explor…
ClusteringGraph MatchingRetrievalSDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences
This paper presents a novel randomized algorithm for robust point cloud registration without correspondences. Most existing registration approaches require a set of putative correspondences obtained by extracting invaria…
Graph MatchingPoint Cloud Registration