LightGlue: Local Feature Matching at Light Speed (ICCV 2023)
image-matching 开源项目推荐(209 个)
image-matching 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 209 个仓库Implementation of XFeat (CVPR 2024). Do you need robust and fast local feature extraction? You are in the right place!
使用Github Action每天自动更新简历论文
[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.
收件箱图像匹配webui
Training library for local feature detection and matching
🔥SLAM, VIsual localization, keypoint detection, Image matching, Pose/Object tracking, Depth/Disparity/Flow Estimation, 3D-graphic, etc. related papers and code
Wrapper of 50+ image matching models with a unified interface
GIM: Learning Generalizable Image Matcher From Internet Videos (ICLR 2024 Spotlight)
Code release for CVPR'24 submission 'OmniGlue'
[CVPR 2025] MINIMA: Modality Invariant Image Matching
Joint Deep Matcher for Points and Lines 🖼️💥🖼️ (ICCV 2023)
这是一个工具箱库,用于评估从一对图像进行图像匹配的各种方法。
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.
Hardnet descriptor model - "Working hard to know your neighbor's margins: Local descriptor learning loss"
[CVPR 2023] DKM: Dense Kernelized Feature Matching for Geometry Estimation
[NeurIPS 2026] Official implementation of paper "VLM³: Vision Language Models Are Native 3D Learners".
Bibliographic list for papers of image matching
Open Source Graph Neural Net Based Pipeline for Image Matching
A personal list of papers and resources of image matching and pose estimation, including perspective images and panoramas.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/image-matching。
- 该话题在 GitHub 上共有 209 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 2.1 万 Star,覆盖 2 种主要语言,数据更新于 2026-11-07。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。