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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},…
The main features of cvlab-epfl/disk are: Local Feature Matching.
Projects with overlapping indexed features include: openmvg/openmvg — openMVG is a computer vision geometry library and toolkit for multiple view geometry. It serves as a framework for… kornia/kornia — Kornia is a differentiable computer vision library and cross-framework tensor vision toolset. It implements vision… cvg/hierarchical-localization — This project is a 3D visual localization framework designed to determine a camera's exact position and orientation by… colmap/colmap — COLMAP is a 3D scene reconstruction suite and C++ geometry library that implements a full structure-from-motion… opencv/opencv_contrib — This project is a collection of optional, community-contributed algorithms and specialized vision tools that extend… hybridgroup/gocv — GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and…
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
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
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
openMVG is a computer vision geometry library and toolkit for multiple view geometry. It serves as a framework for structure from motion and 3D scene reconstruction, providing the tools necessary to recover 3D point clouds and camera poses from collections of 2D images. The library implements both global and incremental structure-from-motion pipelines. It uses geometric algorithms to calculate camera pose estimation and image localization, employing Levenberg-Marquardt bundle adjustment to refine 3D coordinates and camera parameters by minimizing reprojection error. The project covers a broa