In this paper, the authors introduced SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points. Many works on deep…
What does 2021 hold for Graph ML?, by Michael Bronstein
Review: SuperGlue: Learning Feature Matching with Graph Neural Networks, by Vinh Quang Tran, XuLab
SuperGluePretrainedNetwork/models/superglue.py at master · magicleap/SuperGluePretrainedNetwork · GitHub
Predicting cognitive scores with graph neural networks through sample selection learning
Transformers in Computer Vision: why not ?, by Duong Nguyen
SuperGlue: Learning Feature Matching With Graph Neural Networks
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Review: SuperGlue: Learning Feature Matching with Graph Neural Networks, by Vinh Quang Tran, XuLab
Research Paper Deep Dive - Vision GNN: An Image is Worth Graph of Nodes
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Semantic Segmentation using mmsegmentation, by minhduc
GLMNet: Graph learning-matching convolutional networks for feature matching - ScienceDirect
Scene text detection — trends in brief, by Chu Pi, XuLab
Review: SuperGlue: Learning Feature Matching with Graph Neural Networks, by Vinh Quang Tran, XuLab
A Practical Tutorial on Graph Neural Networks