superglue
There are 4 repositories under superglue topic.
- Hierarchical-Localization
cvg / Hierarchical-Localization
Visual localization made easy with hloc
Language:Python 2859 yingxin-jia / SuperGlue-pytorch
[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.
Language:Python 511- image-matching-webui
Vincentqyw / image-matching-webui
🤗 image matching toolbox webui
Language:Python 502 - Language:C++ 462
xmba15 / onnx_runtime_cpp
small c++ library to quickly deploy models using onnxruntime
Language:C++ 2833DOM-FBK / deep-image-matching
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.
Language:Python 254Broad-sky / feature-detection-matching-algorithm
🚀 Deep learning includes superpoint-superglue(C++, TensorRT), and traditional algorithms include zkaze, surf, ORB, etc.
Language:C++ 236yuefanhao / SuperPoint-SuperGlue-TensorRT
SuperPoint and SuperGlue with TensorRT. Deploy with C++.
Language:C++ 182feixue94 / imp-release
[CVPR 2023] IMP: iterative matching and pose estimation with transformer-based recurrent module
Language:Python 1284ku / Place-recognition-evaluation
Benchmarking and evaluation framework for place recognition methods, featuring SuperPoint+SuperGlue, LoGG3D-Net, Scan Context, DBoW2, MixVPR, STD
Language:C++ 68- finetuning-scheduler
speediedan / finetuning-scheduler
A PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.
Language:Python 55 adityamwagh / SuperSLAM
SuperSLAM: Open Source Framework for Deep Learning based Visual SLAM (Work in Progress)
Language:C++ 43KopanevPavel / SuperGlue_ROS
ROS wrapper for SuperGlue and SuperPoint models
Language:Python 32jomariya23156 / SuperGlue-for-Visual-Place-Recognition
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.
Language:Jupyter Notebook 30- Language:C++ 26
oym1994 / ImageFeaturesAndMatching
Image features and related matching methods
Language:C++ 24atfortes / ImageMatchingChallenge2022
CVPR 2022 "Image Matching: Local Features and Beyond" workshop challenge: Kaggle Silver Medal solution (34th out of 642 teams).
Language:Jupyter Notebook 19SungJaeShin / Feature_matching
The implementation about feature matching using various method !!
Language:C++ 16- Language:C++ 16
bimalka98 / Stitch-images-using-SuperGlue-GNN
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)}
Language:Jupyter Notebook 13nishiwen1214 / SuperGLUE-bert4keras
基于bert4keras的SuperGLUE基准代码
Language:Python 13MarkNaeem / VSLAM-playground
Building a full Visual SLAM pipeline to experiment with different techniques
Language:Python 10🦆 A simple sinkhorn algorithm to solve optimal transport problem writen in Matlab
Language:MATLAB 8- Language:Python 6
simple library to make life easy when deploying superpoint, superglue models
Language:Jupyter Notebook 5viniavskyi-ostap / superglue-lightning
SuperGlue training pipeline written using Pytorch Lightning
Language:Python 2- Kaboom
zer0Kerbal / Kaboom
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.
Language:C# 2 Bachfischer / COMP90086-Fine-grained-localisation
Source code for COMP90086 Project 2021
Language:Jupyter Notebook 1dana4056 / Ta-da-world
GPS기반 온라인 보물찾기 게임 서비스입니다
Language:TypeScript 1rishabhpahuja / Wombat
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.
Language:Python 1Coarse-to-Fine High Resolution Image Alignment/Registration
Language:C++ 1manyue-zhang / Superglue-based-image-analysis
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.
Language:Python 0mhdr3a / transformers-diagnostics
Model Evaluation using SuperGLUE Diagnostic Dataset
Language:Pythonsubhalingamd / nlp-contextual-word-meaning-comparision
Evaluating context-sensitive word meaning understanding in pair of sentences for BERT and GloVe+BiLSTM using WiC dataset | A3 for COL772 course (Fall 21)
Language:Jupyter Notebook
