📝Awesome and classical image retrieval papers

Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place!

D2-Net: A Trainable CNN for Joint Description and Detection of Local Features

My personal note about local and global descriptor

Joint Deep Matcher for Points and Lines 🖼️💥🖼️ (ICCV 2023)

Code for the CVPR2021 paper "Patch-NetVLAD: Multi-Scale Fusion of Locally-Global Descriptors for Place Recognition"

ONNX-compatible LightGlue: Local Feature Matching at Light Speed. Supports TensorRT, OpenVINO

A framework to easily use 32 (and growing) different image matching methods

Open Source Graph Neural Net Based Pipeline for Image Matching

PyTorch Implementation of "Large-Scale Image Retrieval with Attentive Deep Local Features"

Code and weights for local feature affine shape estimation paper "Repeatability Is Not Enough: Learning Discriminative Affine Regions via Discriminability"

ELSED: Enhanced Line SEgment Drawing

Baselines for the Image Matching Benchmark and Challenge

Comparative Evaluation of Hand-Crafted and Learned Local Features

PyTorch implementation of SIFT descriptor

🚀🚀 Revisiting Binary Local Image Description for Resource Limited Devices

[CVPR 2023] SFD2: Semantic-guided Feature Detection and Description. Embedding semantics into local features implicitly for long-term visual localization

[CVPR2022] Decoupling Makes Weakly Supervised Local Feature Better

HOW local descriptors

MODS (Matching On Demand with view Synthesis) is algorithm for wide-baseline matching.