Papers Graph Matching
“Graph Matching” 태그가 달린 논문 515편 · 필터 해제
Neural Graph Matching for Pre-training Graph Neural Networks
Recently, graph neural networks (GNNs) have been shown powerful capacity at modeling structural data. However, when adapted to downstream tasks, it usually requires abundant task-specific labeled data, which can be extre…
Graph MatchingOptimal Transport-based Graph Matching for 3D retinal OCT image registration
Registration of longitudinal optical coherence tomography (OCT) images assists disease monitoring and is essential in image fusion applications. Mouse retinal OCT images are often collected for longitudinal study of eye …
Graph MatchingImage RegistrationRandom Graph Matching in Geometric Models: the Case of Complete Graphs
This paper studies the problem of matching two complete graphs with edge weights correlated through latent geometries, extending a recent line of research on random graph matching with independent edge weights to geometr…
Graph MatchingA Graph-Matching Approach for Cross-view Registration of Over-view 2 and Street-view based Point Clouds
In this paper, based on the assumption that the object boundaries (e.g., buildings) from the over-view data should coincide with footprints of fa\c{c}ade 3D points generated from street-view photogrammetric images, we ai…
global-optimizationGraph MatchingSIGMA: A Structural Inconsistency Reducing Graph Matching Algorithm
Graph matching finds the correspondence of nodes across two correlated graphs and lies at the core of many applications. When graph side information is not available, the node correspondence is estimated on the sole basi…
Graph MatchingGraph Neural Networks for Cross-Camera Data Association
Cross-camera image data association is essential for many multi-camera computer vision tasks, such as multi-camera pedestrian detection, multi-camera multi-target tracking, 3D pose estimation, etc. This association task …
3D Pose EstimationGraph MatchingPedestrian DetectionPose EstimationLightweight Object-level Topological Semantic Mapping and Long-term Global Localization based on Graph Matching
Mapping and localization are two essential tasks for mobile robots in real-world applications. However, largescale and dynamic scenes challenge the accuracy and robustness of most current mature solutions. This situation…
Graph MatchingManagementBilingual Lexicon Induction for Low-Resource Languages using Graph Matching via Optimal Transport
Bilingual lexicons form a critical component of various NLP applications, including unsupervised and semisupervised machine translation and crosslingual information retrieval. In this work, we improve bilingual lexicon i…
Bilingual Lexicon InductionGraph MatchingInformation RetrievalMachine Translation+2Training Free Graph Neural Networks for Graph Matching
We present a framework of Training Free Graph Matching (TFGM) to boost the performance of Graph Neural Networks (GNNs) based graph matching, providing a fast promising solution without training (training-free). TFGM prov…
Entity AlignmentGraph MatchingKnowledge GraphsDeep Probabilistic Graph Matching
Most previous learning-based graph matching algorithms solve the \textit{quadratic assignment problem} (QAP) by dropping one or more of the matching constraints and adopting a relaxed assignment solver to obtain sub-opti…
Graph MatchingAppearance and Structure Aware Robust Deep Visual Graph Matching: Attack, Defense and Beyond
Despite the recent breakthrough of high accuracy deep graph matching (GM) over visual images, the robustness of deep GM models is rarely studied which yet has been revealed an important issue in modern deep nets, ran…
Adversarial AttackData AugmentationGraph LearningGraph MatchingA Graph Matching Perspective With Transformers on Video Instance Segmentation
Video Instance Segmentation (VIS) needs to automatically track and segment multiple objects in videos that rely on modeling the spatial-temporal interactions of the instances. This paper presents a graph matching-bas…
Graph MatchingInstance SegmentationSemantic SegmentationVideo Instance SegmentationGraph-Context Attention Networks for Size-Varied Deep Graph Matching
Deep learning for graph matching has received growing interest and developed rapidly in the past decade. Although recent deep graph matching methods have shown excellent performance on matching between graphs of equa…
Graph MatchingBilateral Cross-Modality Graph Matching Attention for Feature Fusion in Visual Question Answering
Answering semantically-complicated questions according to an image is challenging in Visual Question Answering (VQA) task. Although the image can be well represented by deep learning, the question is always simply embedd…
Graph MatchingQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)Robust Partial-to-Partial Point Cloud Registration in a Full Range
Point cloud registration for 3D objects is a challenging task due to sparse and noisy measurements, incomplete observations and large transformations. In this work, we propose \textbf{G}raph \textbf{M}atching \textbf{C}o…
Graph MatchingPoint Cloud RegistrationRiemannian Functional Map Synchronization for Probabilistic Partial Correspondence in Shape Networks
We consider the problem of graph-matching on a network of 3D shapes with uncertainty quantification. We assume that the pairwise shape correspondences are efficiently represented as \emph{functional maps}, that match rea…
Graph MatchingUncertainty QuantificationCross-domain Named Entity Recognition via Graph Matching
Cross-domain NER is a practical yet challenging problem since the data scarcity in the real-world scenario. A common practice is first to learn a NER model in a rich-resource general domain and then adapt the model to sp…
Cross-Domain Named Entity RecognitionFew-Shot LearningGraph MatchingMulti-Task Learning+5Independent SE(3)-Equivariant Models for End-to-End Rigid Protein Docking
Protein complex formation is a central problem in biology, being involved in most of the cell's processes, and essential for applications, e.g. drug design or protein engineering. We tackle rigid body protein-protein doc…
Drug DesignGraph MatchingTranslationSPA-GCN: Efficient and Flexible GCN Accelerator with an Application for Graph Similarity Computation
While there have been many studies on hardware acceleration for deep learning on images, there has been a rather limited focus on accelerating deep learning applications involving graphs. The unique characteristics of gr…
CPUDeep LearningGPUGraph Matching+2Graph Matching via Optimal Transport
The graph matching problem seeks to find an alignment between the nodes of two graphs that minimizes the number of adjacency disagreements. Solving the graph matching is increasingly important due to it's applications in…
Graph Matching