awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
cvg avatar

cvg/Hierarchical-Localization

0
View on GitHub↗
3,961 stars·727 forks·Python·apache-2.0·19 views

Hierarchical Localization

This project is a 3D visual localization framework designed to determine a camera's exact position and orientation by matching 2D image features against a 3D reference model. It includes a structure-from-motion pipeline to reconstruct 3D scene geometry from unordered image sets, creating the necessary spatial maps for localization.

The system employs a hierarchical coarse-to-fine localization approach. This process begins with a global-descriptor image retrieval system to identify candidate reference images from a large database and progresses through local feature matching to final 3D model alignment using perspective-n-point pose estimation.

The framework covers deep learning-based feature extraction, sparse feature matching, and camera model calibration to ensure accurate 3D reconstruction. It also provides tools for localization data visualization and 3D scene analysis to examine keypoint visibility and debug mapping errors.

Features

  • Visual Localization - Determines a camera's exact position and orientation by matching live images against a 3D reference model.
  • 3D Pose Estimation - Calculates precise camera position and orientation by solving the transformation between 2D points and 3D coordinates.
  • Visual Localization Frameworks - Provides a complete system for determining camera poses by matching 2D features against 3D reference models.
  • Pose Refinement Pipelines - Refines camera pose by progressing from global retrieval to local matching and 3D model alignment.
  • Visual Feature Extractors - Uses neural networks to generate robust image descriptors stable across different lighting and viewpoints.
  • Feature Extraction - Identifies local keypoints and descriptors from images using deep learning and traditional computer vision.
  • Deep Feature Extractors - Identifies local keypoints and descriptors in images using neural network based computer vision.
  • Pose Estimation - Calculates the precise location and angle of a device within a mapped environment using visual features.
  • Structure From Motion - Generates sparse 3D models from unordered image sets to serve as reference maps for localization.
  • Local Feature Matching - Establishes geometric correspondences between images using local descriptors and RANSAC verification.
  • Image Retrieval Systems - Filters large image databases using high-level feature vectors to identify candidate reference images.
  • Large-Scale Image Retrieval - Uses global descriptors to quickly identify the most relevant reference images from a large database.
  • Camera Calibration - Defines camera intrinsic parameters to ensure accuracy in 3D reconstruction and pose estimation.
  • Feature Detection and Matching - Toolbox for hierarchical localization using global and local feature matching.
  • Simultaneous Localization and Mapping - Modular toolbox for 6-DoF visual localization.

Star history

Star history chart for cvg/hierarchical-localizationStar history chart for cvg/hierarchical-localization

How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Open-source alternatives to Hierarchical Localization

Similar open-source projects, ranked by how many features they share with Hierarchical Localization.
  • colmap/colmapcolmap avatar

    colmap/colmap

    12,014View on GitHub↗

    COLMAP is a 3D scene reconstruction suite and C++ geometry library that implements a full structure-from-motion pipeline. It functions as a GPU-accelerated photogrammetry tool and multi-view stereo framework designed to produce dense 3D geometry and watertight meshes from collections of 2D images. The project distinguishes itself through hardware-accelerated feature extraction and a modular camera modeling system that supports perspective, fisheye, and equirectangular lens types. It employs vocabulary tree image retrieval to efficiently identify similar images in large datasets and provides P

    C++
    View on GitHub↗12,014
  • kornia/korniakornia avatar

    kornia/kornia

    11,238View on GitHub↗

    Kornia 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

    Pythonartificial-intelligencecomputer-visiondeep-learning
    View on GitHub↗11,238
  • paddlepaddle/paddleclasPaddlePaddle avatar

    PaddlePaddle/PaddleClas

    5,816View on GitHub↗

    PaddleClas is a toolkit for image classification and recognition built on PaddlePaddle. It provides a suite of tools for training deep learning models and a framework for implementing visual search and retrieval systems. The project includes a computer vision model optimization suite and tools for cross-platform deployment. It enables the export of trained models to servers, mobile devices, and edge hardware to achieve high-performance inference across different programming languages. The toolkit covers model compression and optimization through pruning, quantization, and knowledge distillat

    Pythonautoaugmentcutmixdeit
    View on GitHub↗5,816
  • zju3dv/easymocapzju3dv avatar

    zju3dv/EasyMocap

    4,483View on GitHub↗

    EasyMocap is a markerless 3D human motion capture system that recovers body, hand, and face poses from single or multi-view video without physical markers or suits. It uses parametric body models like SMPL, SMPL-X, and MANO, and leverages mirror reflections to resolve depth ambiguity in single-view pose estimation, improving accuracy by computing mirror surface normals from vanishing points. The system distinguishes itself through mirror-assisted depth disambiguation, enabling accurate 3D pose reconstruction from a single RGB image or video that includes a mirror reflection. It also supports

    Pythonmotion-capture
    View on GitHub↗4,483
See all 30 alternatives to Hierarchical Localization→

Frequently asked questions

What does cvg/hierarchical-localization do?

This project is a 3D visual localization framework designed to determine a camera's exact position and orientation by matching 2D image features against a 3D reference model. It includes a structure-from-motion pipeline to reconstruct 3D scene geometry from unordered image sets, creating the necessary spatial maps for localization.

What are the main features of cvg/hierarchical-localization?

The main features of cvg/hierarchical-localization are: Visual Localization, 3D Pose Estimation, Visual Localization Frameworks, Pose Refinement Pipelines, Visual Feature Extractors, Feature Extraction, Deep Feature Extractors, Pose Estimation.

What are some open-source alternatives to cvg/hierarchical-localization?

Open-source alternatives to cvg/hierarchical-localization include: colmap/colmap — COLMAP is a 3D scene reconstruction suite and C++ geometry library that implements a full structure-from-motion… kornia/kornia — Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision… zju3dv/easymocap — EasyMocap is a markerless 3D human motion capture system that recovers body, hand, and face poses from single or… paddlepaddle/paddleclas — PaddleClas is a toolkit for image classification and recognition built on PaddlePaddle. It provides a suite of tools… openmvg/openmvg — openMVG is a computer vision geometry library and toolkit for multiple view geometry. It serves as a framework for… fchollet/deep-learning-models — This project is a collection of deep learning tools for image classification and audio tagging, providing a repository…