SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
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Updated
Aug 30, 2024 - Python
SuperGlue: Learning Feature Matching with Graph Neural Networks (CVPR 2020, Oral)
Visual localization made easy with hloc
Code for "LoFTR: Detector-Free Local Feature Matching with Transformers", CVPR 2021, T-PAMI 2022
Pixel-Perfect Structure-from-Motion with Featuremetric Refinement (ICCV 2021, Best Student Paper Award)
A clean and concise Python implementation of SIFT (Scale-Invariant Feature Transform)
🤗 image matching toolbox webui
[CVPR 2024] RoMa: Robust Dense Feature Matching; RoMa is the robust dense feature matcher capable of estimating pixel-dense warps and reliable certainties for almost any image pair.
[CVPR 2023] DKM: Dense Kernelized Feature Matching for Geometry Estimation
ONNX-compatible LightGlue: Local Feature Matching at Light Speed. Supports TensorRT, OpenVINO
[CVPR 2020, Oral] MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask
Patch2Pix: Epipolar-Guided Pixel-Level Correspondences [CVPR2021]
Code to easily try 30 (and growing) different image matching methods
SuperPoint and SuperGlue with TensorRT. Deploy with C++.
💎 "Marker-less Augmented Reality" with OpenCV and OpenGL.
A framework for building high-performance real-time multiple object trackers
Feature Detection and Matching with SIFT, SURF, KAZE, BRIEF, ORB, BRISK, AKAZE and FREAK through the Brute Force and FLANN algorithms using Python and OpenCV
Python (Pytorch) and Matlab (MatConvNet) implementations of CVPR 2021 Image Matching Workshop paper DFM: A Performance Baseline for Deep Feature Matching
Interactive code for image similarity using SIFT algorithm
Integrate SuperPoint and LightGlue into OpenCV image stitching or Matching algorithm
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