Papers Graph Matching
“Graph Matching” 태그가 달린 논문 515편 · 필터 해제
Robust Graph Matching Using An Unbalanced Hierarchical Optimal Transport Framework
Graph matching is one of the most significant graph analytic tasks, which aims to find the node correspondence across different graphs. Most existing graph matching approaches mainly rely on topological information, whos…
cross-modal alignmentGraph MatchingGraphAlign: Enhancing Accurate Feature Alignment by Graph matching for Multi-Modal 3D Object Detection
LiDAR and cameras are complementary sensors for 3D object detection in autonomous driving. However, it is challenging to explore the unnatural interaction between point clouds and images, and the critical factor is how t…
3D Object DetectionAutonomous DrivingGraph Matchingobject-detection+2Clustering-based Image-Text Graph Matching for Domain Generalization
Learning domain-invariant visual representations is important to train a model that can generalize well to unseen target task domains. Recent works demonstrate that text descriptions contain high-level class-discriminati…
ClusteringDomain GeneralizationGraph ClusteringGraph Matching+1PharmacoNet: Accelerating Large-Scale Virtual Screening by Deep Pharmacophore Modeling
As the size of accessible compound libraries expands to over 10 billion, the need for more efficient structure-based virtual screening methods is emerging. Different pre-screening methods have been developed for rapid sc…
Drug DiscoveryGraph MatchingInstance SegmentationPose Prediction+1GraphEcho: Graph-Driven Unsupervised Domain Adaptation for Echocardiogram Video Segmentation
Echocardiogram video segmentation plays an important role in cardiac disease diagnosis. This paper studies the unsupervised domain adaption (UDA) for echocardiogram video segmentation, where the goal is to generalize the…
Domain AdaptationGraph MatchingSegmentationUnsupervised Domain Adaptation+2CATS: Conditional Adversarial Trajectory Synthesis for Privacy-Preserving Trajectory Data Publication Using Deep Learning Approaches
The prevalence of ubiquitous location-aware devices and mobile Internet enables us to collect massive individual-level trajectory dataset from users. Such trajectory big data bring new opportunities to human mobility res…
EthicsGraph MatchingPrivacy PreservingAGMDT: Virtual Staining of Renal Histology Images with Adjacency-Guided Multi-Domain Transfer
Renal pathology, as the gold standard of kidney disease diagnosis, requires doctors to analyze a series of tissue slices stained by H&E staining and special staining like Masson, PASM, and PAS, respectively. These specia…
Graph MatchingStyle TransferVirtual StainingSSIG: A Visually-Guided Graph Edit Distance for Floor Plan Similarity
We propose a simple yet effective metric that measures structural similarity between visual instances of architectural floor plans, without the need for learning. Qualitatively, our experiments show that the retrieval re…
Graph MatchingMetric LearningRecommendation SystemsRetrievalExplaining Vision and Language through Graphs of Events in Space and Time
Artificial Intelligence makes great advances today and starts to bridge the gap between vision and language. However, we are still far from understanding, explaining and controlling explicitly the visual content from a l…
Graph MatchingVideo GenerationGotta match 'em all: Solution diversification in graph matching matched filters
We present a novel approach for finding multiple noisily embedded template graphs in a very large background graph. Our method builds upon the graph-matching-matched-filter technique proposed in Sussman et al., with the …
AllGraph MatchingAn approach based on Open Research Knowledge Graph for Knowledge Acquisition from scientific papers
A scientific paper can be divided into two major constructs which are Metadata and Full-body text. Metadata provides a brief overview of the paper while the Full-body text contains key-insights that can be valuable to fe…
Graph MatchingQuestion AnsweringHyper Association Graph Matching with Uncertainty Quantification for Coronary Artery Semantic Labeling
Coronary artery disease (CAD) is one of the primary causes leading to death worldwide. Accurate extraction of individual arterial branches on invasive coronary angiograms (ICA) is important for stenosis detection and CAD…
Decision MakingGraph MatchingSemantic SegmentationUncertainty QuantificationShape-Graph Matching Network (SGM-net): Registration for Statistical Shape Analysis
This paper focuses on the statistical analysis of shapes of data objects called shape graphs, a set of nodes connected by articulated curves with arbitrary shapes. A critical need here is a constrained registration of po…
Graph MatchingImproving ICD-based semantic similarity by accounting for varying degrees of comorbidity
Finding similar patients is a common objective in precision medicine, facilitating treatment outcome assessment and clinical decision support. Choosing widely-available patient features and appropriate mathematical metho…
Graph MatchingSemantic SimilaritySemantic Textual SimilarityDeep Semantic Graph Matching for Large-scale Outdoor Point Clouds Registration
Current point cloud registration methods are mainly based on local geometric information and usually ignore the semantic information contained in the scenes. In this paper, we treat the point cloud registration problem a…
Graph MatchingPoint Cloud RegistrationSemantic SegmentationLearning Scene-Pedestrian Graph for End to end Person Search
Person search aims to find specific persons from visual scenes, including two subtasks, pedestrian detection, and person reidentification. The dominant fashion in this area is end-to-end networks that focus on analyzing …
Graph MatchingPedestrian DetectionPerson SearchCo-attention Graph Pooling for Efficient Pairwise Graph Interaction Learning
Graph Neural Networks (GNNs) have proven to be effective in processing and learning from graph-structured data. However, previous works mainly focused on understanding single graph inputs while many real-world applicatio…
Graph MatchingMultiscale Dynamic Graph Representation for Biometric Recognition with Occlusions
Occlusion is a common problem with biometric recognition in the wild. The generalization ability of CNNs greatly decreases due to the adverse effects of various occlusions. To this end, we propose a novel unified framewo…
Graph MatchingUnsupervised Deep Graph Matching Based on Cycle Consistency
We contribute to the sparsely populated area of unsupervised deep graph matching with application to keypoint matching in images. Contrary to the standard \emph{supervised} approach, our method does not require ground tr…
Graph MatchingBlind Graph Matching Using Graph Signals
Classical graph matching aims to find a node correspondence between two unlabeled graphs of known topologies. This problem has a wide range of applications, from matching identities in social networks to identifying simi…
Graph Matching