There are 4 repositories under superglue topic.
Visual localization made easy with hloc
🤗 image matching toolbox webui
[SuperGlue: Learning Feature Matching with Graph Neural Networks] This repo includes PyTorch code for training the SuperGlue matching network on top of SIFT keypoints and descriptors.
Multiview matching with deep-learning and hand-crafted local features for COLMAP and other SfM software. Supports high-resolution formats and images with rotations. Both CLI and GUI are supported.
small c++ library to quickly deploy models using onnxruntime
🚀 Deep learning includes superpoint-superglue(C++, TensorRT), and traditional algorithms include zkaze, surf, ORB, etc.
SuperPoint and SuperGlue with TensorRT. Deploy with C++.
[CVPR 2023] IMP: iterative matching and pose estimation with transformer-based recurrent module
Benchmarking and evaluation framework for place recognition methods, featuring SuperPoint+SuperGlue, LoGG3D-Net, Scan Context, DBoW2, MixVPR, STD
SuperSLAM: Open Source Framework for Deep Learning based Visual SLAM (Work in Progress)
A PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
Using SuperGlue (from Magic Leap team) in Visual Place Recognition tasks. Providing full workflow from videos/images to end-to-end API and step-by-step how to use all codes.
ROS wrapper for SuperGlue and SuperPoint models
Image features and related matching methods
The implementation about feature matching using various method !!
CVPR 2022 "Image Matching: Local Features and Beyond" workshop challenge: Kaggle Silver Medal solution (34th out of 642 teams).
Stitch images using SuperGlue features instead of mouse-clicked points. Compute the homography through RANSAC or MSAC. Stitch more than two images using mouse-clicked points. Handle the seams. {SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)}
Vision-based GNSS-Free Localization for UAVs in the Wild
Building a full Visual SLAM pipeline to experiment with different techniques
基于bert4keras的SuperGLUE基准代码
🦆 A simple sinkhorn algorithm to solve optimal transport problem writen in Matlab
simple library to make life easy when deploying superpoint, superglue models
image stitching using superglue
SuperGlue training pipeline written using Pytorch Lightning
Another way to not go to space today! What can be more Kerbal than more Explosions!* *Now with SuperKlue Implosions!* KaboOom! (BOOM) is an add-on for Kerbal Space Program.
Source code for COMP90086 Project 2021
GPS기반 온라인 보물찾기 게임 서비스입니다
This repository consists of two major components for a project called E-waste recycling system. One component is used to generate a labelled dataset to train U-Net segmentation network. The second component is used to perform non-rigid registration using Demon's algorithm.
Coarse-to-Fine High Resolution Image Alignment/Registration
This project uses the model from the paper SuperGlue: Learning Feature Matching with Graph Neural Networks and builds on it to implement an analysis of the images returned by the Hand-Up Display. In this project, significant results have been achieved on challenging "complex" geometric images.
This project involves analyzing and classifying the BoolQ dataset from the SuperGLUE benchmark. We implemented various classifiers and techniques, including rules-based logic, BERT, RNN, and GPT-3/4 data augmentation, achieving performance improvements.
Model Evaluation using SuperGLUE Diagnostic Dataset