danini/graph-cut-ransac
C++ implementation of the Graph-Cut RANSAC algorithm for robust estimation of geometric models (homography, fundamental matrix, essential matrix) from image data.
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This repository provides an implementation of the Graph-Cut RANSAC algorithm published at CVPR 2018. The algorithm performs robust estimation of geometric transformations between image pairs by iteratively sampling correspondences and optimizing via graph-cut. It estimates homographies, fundamental matrices, and essential matrices used in camera pose estimation and multi-view geometry tasks. A Python wrapper (pygcransac) is also available via PyPI.
Frequently asked
- What is danini/graph-cut-ransac?
- C++ implementation of the Graph-Cut RANSAC algorithm for robust estimation of geometric models (homography, fundamental matrix, essential matrix) from image data.
- Is graph-cut-ransac open source?
- Yes — danini/graph-cut-ransac is an open-source project tracked on heatdrop.
- What language is graph-cut-ransac written in?
- danini/graph-cut-ransac is primarily written in C++.
- How popular is graph-cut-ransac?
- danini/graph-cut-ransac has 469 stars on GitHub.
- Where can I find graph-cut-ransac?
- danini/graph-cut-ransac is on GitHub at https://github.com/danini/graph-cut-ransac.