Local feature matching
For local feature matching, the first results are magicleap/supergluepretrainednetwork (This repository provides pre-trained deep learning models and geometric tools for local image feature matching and spatial alignment, though it focuses on matching rather than full keypoint extraction), cvg/lightglue (LightGlue is a deep learning-based local feature matching library that computes correspondences between image keypoints using attention mechanisms and dynamic network pruning) and kornia/kornia (Kornia is a differentiable computer vision library that provides deep learning-based and traditional image processing utilities, including keypoint detection and geometric verification modules suitable for feature matching pipelines). hanxf/matchnet and gtolias/how round out the shortlist. Compare the match explanations and check the project documentation against your requirements.
Compare open-source GitHub repositories for local feature matching to identify matching keypoints in images for computer vision.
Local feature matching
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- magicleap/supergluepretrainednetwork
magicleap/SuperGluePretrainedNetwork
4,035View on GitHubThis project is a collection of neural network models and geometric tools designed for image feature matching, spatial alignment, and visual localization. It provides a pre-trained neural network model for identifying high-accuracy correspondences between sparse image features without requiring local training. The system utilizes a graph neural network matcher that employs attention mechanisms and message passing to learn spatial relationships between image feature points. It integrates a RANSAC camera pose estimator to filter feature matches and calculate the relative spatial transformation
This repository provides pre-trained deep learning models and geometric tools for local image feature matching and spatial alignment, though it focuses on matching rather than full keypoint extraction.
PythonGeometricImage Pair MatchingFeature Correspondence - cvg/lightglue
cvg/LightGlue
4,625View on GitHubLightGlue is a deep learning framework designed for local feature matching and high-speed correspondence estimation between pairs of images. It functions as a computer vision matching model that identifies corresponding keypoints across different viewpoints. The system utilizes an adaptive neural network architecture that dynamically optimizes inference speed by pruning its own depth and width based on the input image pairs. This approach employs a transformer-style attention mechanism and cross-image attention to compute correlations between feature descriptors. The matching process include
LightGlue is a deep learning-based local feature matching library that computes correspondences between image keypoints using attention mechanisms and dynamic network pruning.
PythonDeep Feature Matchers - kornia/kornia
kornia/kornia
11,238View on GitHubKornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision operations as differentiable tensors to enable integration into deep learning pipelines and supports the transpilation of operations across PyTorch, TensorFlow, JAX, and NumPy. The project provides specialized toolsets for geometric vision and stereo depth, including algorithms for 3D scene reconstruction, camera calibration, and pose estimation. It further distinguishes itself as a differentiable image augmentation framework, applying random geometric and color transformations w
Kornia is a differentiable computer vision library that provides deep learning-based and traditional image processing utilities, including keypoint detection and geometric verification modules suitable for feature matching pipelines.
PythonFeature Extraction - hanxf/matchnet
hanxf/matchnet
Matchnet is a deep learning approach for patch-based local image matching, which jointly learns feature representation and matching function from data. More details about this approach can be found in our CVPR'15 paper.
MatchNet provides a deep learning approach for patch-based local image matching that jointly learns feature representation and matching functions, serving as a specialised local feature matching library.
PythonLocal Feature Matching - gtolias/how
gtolias/how
This is the official Python/PyTorch implementation of the HOW local descriptors from our ECCV 2020 paper:
This repository provides a PyTorch implementation of local descriptors for image matching and retrieval from a published research paper, fitting the requested category well despite lacking some broader features like real-time performance or traditional descriptors.
PythonLocal Feature Matching - cvlab-epfl/disk
cvlab-epfl/disk
Official code release for DISK: learning local features with policy gradient. If you use this code in your work, please cite us as ``latex @article{tyszkiewicz2020disk, title={DISK: Learning local features with policy gradient}, author={Tyszkiewicz, Micha{\l} and Fua, Pascal and Trulls, Eduard},…
DISK provides learned local features trained with policy gradient for keypoint extraction and matching, fitting the deep learning approach of this search domain.
PythonLocal Feature Matching - dagnyt/hardnet
DagnyT/hardnet
This repository provides a deep learning-based local feature descriptor for image matching, which fits the category well even though it focuses specifically on the descriptor rather than a full pipeline.
PythonLocal Feature Matching - facebookresearch/silk
facebookresearch/silk
SiLK is a self-supervised framework for learning keypoints. SiLK focuses on simplicity and flexibility, while also providing state-of-art and competitive results on existing benchmarks.
SiLK is a self-supervised local feature extraction framework providing keypoint learning algorithms, though it focuses more on deep learning features rather than traditional descriptors or full retrieval pipelines.
GnuplotLocal Feature Matching - cvg/glue-factory
cvg/glue-factory
1,152View on GitHubGlue Factory is CVG's library for training and evaluating deep neural network that extract and match local visual feature. It enables you to: - Reproduce the training of state-of-the-art models for point and line matching, like LightGlue and GlueStick (ICCV 2023) - Train these models on multiple…
Glue Factory is a specialised library for training and evaluating deep learning models for local image feature extraction and matching, fitting the core category well though focused primarily on machine learning workflows rather than out-of-the-box geometric verification pipelines.
PythonLocal Feature Matching - axelbarroso/key.net
axelBarroso/Key.Net
Code for the ICCV19 paper:
This repository provides a deep learning-based local feature extraction and matching implementation from a published paper, fitting the category even though it lacks a full suite of traditional descriptors and real-time wrappers.
PythonLocal Feature Matching - vlfeat/vlfeat
vlfeat/vlfeat
1,652View on GitHubAn open library of computer vision algorithms
This repository provides classic local feature extraction and matching algorithms like SIFT implemented in C, serving as a well-established traditional computer vision library despite lacking deep learning features.
CMachine Learning
Compare the top 10 at a glance
| Repository | Stars | Language | License | Last push |
|---|---|---|---|---|
| magicleap/supergluepretrainednetwork | 4K | Python | NOASSERTION | |
| cvg/lightglue | 4.6K | Python | Apache-2.0 | |
| kornia/kornia | 11.2K | Python | Apache-2.0 | |
| hanxf/matchnet | 194 | Python | BSD-2-Clause | |
| gtolias/how | 95 | Python | MIT | |
| cvlab-epfl/disk | 387 | Python | Apache-2.0 | |
| dagnyt/hardnet | 528 | Python | mit | |
| facebookresearch/silk | 680 | Gnuplot | GPL-3.0 | |
| cvg/glue-factory | 1.2K | Python | Apache-2.0 | |
| axelbarroso/key.net | 211 | Python | NOASSERTION |