Review: SuperGlue: Learning Feature Matching with Graph Neural

Review: SuperGlue: Learning Feature Matching with Graph Neural

4.9
(144)
Write Review
More
$ 31.50
Add to Cart
In stock
Description

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

Review: Speech-to-Singing Conversion in an Encoder-Decoder Framework, by Nguyenhoang, XuLab

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

Review: Deep mutual Learning. Link to paper…, by Nguyễn Thành Nam

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