Papers Graph Matching
“Graph Matching” 태그가 달린 논문 515편 · 필터 해제
LVM-Med: Learning Large-Scale Self-Supervised Vision Models for Medical Imaging via Second-order Graph Matching
Obtaining large pre-trained models that can be fine-tuned to new tasks with limited annotated samples has remained an open challenge for medical imaging data. While pre-trained deep networks on ImageNet and vision-langua…
Brain Tumor ClassificationContrastive LearningDiabetic Retinopathy GradingGraph Matching+2LIC-GAN: Language Information Conditioned Graph Generative GAN Model
Deep generative models for Natural Language data offer a new angle on the problem of graph synthesis: by optimizing differentiable models that directly generate graphs, it is possible to side-step expensive search proced…
Graph GenerationGraph MatchingLanguage ModellingA polynomial-time iterative algorithm for random graph matching with non-vanishing correlation
We propose an efficient algorithm for matching two correlated Erd\H{o}s--R\'enyi graphs with $n$ vertices whose edges are correlated through a latent vertex correspondence. When the edge density $q= n^{- \alpha+o(1)}$ fo…
Graph MatchingEfficient Algorithms for Exact Graph Matching on Correlated Stochastic Block Models with Constant Correlation
We consider the problem of graph matching, or learning vertex correspondence, between two correlated stochastic block models (SBMs). The graph matching problem arises in various fields, including computer vision, natural…
Graph MatchingAbODE: Ab Initio Antibody Design using Conjoined ODEs
Antibodies are Y-shaped proteins that neutralize pathogens and constitute the core of our adaptive immune system. De novo generation of new antibodies that target specific antigens holds the key to accelerating vaccine d…
Graph MatchingProtein FoldingPromptNER: Prompt Locating and Typing for Named Entity Recognition
Prompt learning is a new paradigm for utilizing pre-trained language models and has achieved great success in many tasks. To adopt prompt learning in the NER task, two kinds of methods have been explored from a pair of s…
Cross-Domain Few-ShotEntity TypingGraph Matchingnamed-entity-recognition+5GEST: the Graph of Events in Space and Time as a Common Representation between Vision and Language
One of the essential human skills is the ability to seamlessly build an inner representation of the world. By exploiting this representation, humans are capable of easily finding consensus between visual, auditory and li…
Graph MatchingText GenerationCoronary Artery Semantic Labeling using Edge Attention Graph Matching Network
Coronary artery disease (CAD) is one of the primary causes leading deaths worldwide. The presence of atherosclerotic lesions in coronary arteries is the underlying pathophysiological basis of CAD, and accurate extraction…
Graph MatchingSemantic SegmentationBi-VLGM : Bi-Level Class-Severity-Aware Vision-Language Graph Matching for Text Guided Medical Image Segmentation
Medical reports with substantial information can be naturally complementary to medical images for computer vision tasks, and the modality gap between vision and language can be solved by vision-language matching (VLM). H…
Graph MatchingImage SegmentationMedical Image SegmentationPrompt Learning+4Image Segmentation via Probabilistic Graph Matching
This work presents an unsupervised and semi-automatic image segmentation approach where we formulate the segmentation as a inference problem based on unary and pairwise assignment probabilities computed using low-level i…
Graph MatchingImage SegmentationSegmentationSemantic Segmentation+1Semantic-Aware Graph Matching Mechanism for Multi-Label Image Recognition
Multi-label image recognition aims to predict a set of labels that present in an image. The key to deal with such problem is to mine the associations between image contents and labels, and further obtain the correct assi…
Few-Shot LearningGraph MatchingMulti-Label Image RecognitionLoop Closure Detection Based on Object-level Spatial Layout and Semantic Consistency
Visual simultaneous localization and mapping (SLAM) systems face challenges in detecting loop closure under the circumstance of large viewpoint changes. In this paper, we present an object-based loop closure detection me…
Graph MatchingLoop Closure DetectionObjectSimultaneous Localization and MappingSelf-Supervised Learning of Object Segmentation from Unlabeled RGB-D Videos
This work proposes a self-supervised learning system for segmenting rigid objects in RGB images. The proposed pipeline is trained on unlabeled RGB-D videos of static objects, which can be captured with a camera carried b…
Contrastive LearningGraph MatchingObjectPoint Cloud Registration+2Deformable Kernel Expansion Model for Efficient Arbitrary-shaped Scene Text Detection
Scene text detection is a challenging computer vision task due to the high variation in text shapes and ratios. In this work, we propose a scene text detector named Deformable Kernel Expansion (DKE), which incorporates t…
Graph MatchingScene Text DetectionSegmentationText DetectionLearnable Graph Matching: A Practical Paradigm for Data Association
Data association is at the core of many computer vision tasks, e.g., multiple object tracking, image matching, and point cloud registration. however, current data association solutions have some defects: they mostly igno…
Graph MatchingGraph Neural NetworkMultiple Object TrackingObject Tracking+1PATS: Patch Area Transportation with Subdivision for Local Feature Matching
Local feature matching aims at establishing sparse correspondences between a pair of images. Recently, detector-free methods present generally better performance but are not satisfactory in image pairs with large scale d…
Graph MatchingOptical Flow EstimationPose EstimationVisual LocalizationSchema Inference for Interpretable Image Classification
In this paper, we study a novel inference paradigm, termed as schema inference, that learns to deductively infer the explainable predictions by rebuilding the prior deep neural network (DNN) forwarding scheme, guided by …
ClassificationGraph Matchingimage-classificationImage ClassificationGraph-based Global Robot Localization Informing Situational Graphs with Architectural Graphs
In this paper, we propose a solution for legged robot localization using architectural plans. Our specific contributions towards this goal are several. Firstly, we develop a method for converting the plan of a building i…
Graph MatchingTexture-Based Input Feature Selection for Action Recognition
The performance of video action recognition has been significantly boosted by using motion representations within a two-stream Convolutional Neural Network (CNN) architecture. However, there are a few challenging problem…
Action RecognitionAnomaly Detectionfeature selectionGraph Matching+7Graph Matching Optimization Network for Point Cloud Registration
Point Cloud Registration is a fundamental and challenging problem in 3D computer vision. Recent works often utilize the geometric structure information in point feature embedding or outlier rejection for registration whi…
Graph MatchingPoint Cloud Registration