Papers Graph Matching
“Graph Matching” 태그가 달린 논문 515편 · 필터 해제
Achieving Almost Exact Recovery in Almost Quadratic Time: Rank-Based Graph Matching via Local Tree Correlation Tests
This paper studies graph matching under the correlated $\text{Erdős-Rényi}$ (ER) graph pair model. This model first samples an $\mathrm{ER}(n,\fracλ{ns})$ base graph, whose edges are then independently subsampled twice w…
Graph MatchingDiffusion enabled Optimal Transport distances for graph matching
This paper introduces Diffusion Semi-Relaxed Fused Gromov-Wasserstein (DsrFGW), a novel method for graph comparison that unifies node features and structural connectivity through optimal transport. While traditional Grom…
Graph MatchingConfidence-feedback-weighted graph matching network: online-offline laser-induced damage site matching under complex interference
Online inspection images of final optics in high-power laser facilities contain pseudo-damage sites that closely resemble true damage sites. Determining the authenticity of online-detected sites is therefore difficult an…
Graph MatchingGraphBEV++: Multi-Modal Feature Alignment for Autonomous Driving
Feature misalignment in BEV perception is a critical yet often overlooked challenge in autonomous driving, especially under calibration uncertainties between LiDAR and camera sensors. To address this issue, we propose a …
Autonomous DrivingGraph MatchingSGM-SLAM: Scene Graph Matching for Data-Efficient Distributed SLAM
We introduce a data-efficient distributed Simultaneous Localization and Mapping (SLAM) framework designed for a team of robots equipped with LiDAR, cameras, and inertial sensors. Our framework uses scene graph matching t…
Graph MatchingPoint CloudsGMN4AD: Graph Matching Network for Alzheimer's Disease Diagnosis with Test-Time Domain Adaptation using Multi-centered Structure Magnetic Resonance Imaging
Alzheimer's Disease (AD) is a progressive neurodegenerative disorder that affects millions of older adults, with prevalence expected to rise significantly in the coming years. Early diagnosis, particularly during the mil…
Contrastive LearningDomain AdaptationGraph MatchingTask-Aware Structured Memory for Dynamic Multi-modal In-Context Learning
Multi-modal large language models (MLLMs) depend on in-context learning (ICL) for rapid task adaptation, but their scalability is severely limited by finite context windows and the growing cost of key-value (KV) caches i…
Graph MatchingGlobally Localizing Lunar Rover in Pixels via Graph Alignment
Precise rover localization is a prerequisite for autonomous lunar exploration, yet the absence of Global Navigation Satellite System (GNSS) signals and the cumulative drift of local localization methods severely constrai…
Zero-shot GeneralizationSemantic SegmentationGraph LearningGraph MatchingSceneGraphGrounder: Zero-Shot 3D Visual Grounding via Structured Scene Graph Matching
Zero-shot 3D visual grounding requires localizing objects in unstructured environments from free-form natural language. Recent vision-language model (VLM) approaches achieve promising results but rely on view-dependent r…
Spatial ReasoningVisual GroundingGraph MatchingAnalogical Trajectory Transfer
We study analogical trajectory transfer, where the goal is to translate motion trajectories in one 3D environment to a semantically analogous location in another. Such a capacity would enable machines to perform analogic…
Spatial ReasoningGraph MatchingTowards Metric-Faithful Neural Graph Matching
Graph Edit Distance (GED) is a fundamental, albeit NP-hard, metric for structural graph similarity. Recent neural graph matching architectures approximate GED by first encoding graphs with a Graph Neural Network (GNN) an…
Graph Neural NetworkGraph SimilarityGraph MatchingLearning-Based Hierarchical Scene Graph Matching for Robot Localization Leveraging Prior Maps
Accurate localization is a fundamental requirement for autonomous robots operating in indoor environments. Scene graphs encode the spatial structure of an environment as a hierarchy of semantic entities and their relatio…
Zero-shot GeneralizationGraph MatchingGraph Construction and Matching for Imperative Programs using Neural and Structural Methods
Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications. In this paper, we focus on graph construction as a foundational step toward this goal. We…
Graph MatchingRobust Graph Matching through Semantic Relationship Generation for SLAM
Graph-based representations such as Scene Graphs enable localization in structured indoor environments by matching a locally observed graph, constructed from sensor data, to a prior map. This process is particularly chal…
Computational EfficiencyGraph MatchingContextual Graph Matching with Correlated Gaussian Features
We investigate contextual graph matching in the Gaussian setting, where both edge weights and node features are correlated across two networks. We derive precise information-theoretic thresholds for exact recovery, and i…
Graph MatchingSeeing Beyond: Extrapolative Domain Adaptive Panoramic Segmentation
Cross-domain panoramic semantic segmentation has attracted growing interest as it enables comprehensive 360° scene understanding for real-world applications. However, it remains particularly challenging due to severe geo…
Semantic SegmentationScene UnderstandingDomain AdaptationGraph MatchingSF3D-RGB: Scene Flow Estimation from Monocular Camera and Sparse LiDAR
Scene flow estimation is an extremely important task in computer vision to support the perception of dynamic changes in the scene. For robust scene flow, learning-based approaches have recently achieved impressive result…
Scene Flow EstimationGraph MatchingPoint CloudsAutoSew: A Geometric Approach to Stitching Prediction with Graph Neural Networks
Automating garment assembly from sewing patterns remains a significant challenge due to the lack of standardized annotation protocols and the frequent absence of semantic cues. Existing methods often rely on panel labels…
Graph Neural NetworkGraph MatchingAn Industrial Dataset for Scene Acquisitions and Functional Schematics Alignment
Aligning functional schematics with 2D and 3D scene acquisitions is crucial for building digital twins, especially for old industrial facilities that lack native digital models. Current manual alignment using images and …
Graph MatchingPoint CloudsMatching and mixing: Matchability of graphs under Markovian error
We consider the problem of graph matching for a sequence of graphs generated under a time-dependent Markov chain noise model. Our edgelighter error model, a variant of the classical lamplighter random walk, iteratively c…
Graph Matching