Pinned Repositories
absolute-pose-from-oriented-and-scaled-features
affine-correspondences-for-camera-geometry
graph-cut-ransac
The Graph-Cut RANSAC algorithm proposed in paper: Daniel Barath and Jiri Matas; Graph-Cut RANSAC, Conference on Computer Vision and Pattern Recognition, 2018. It is available at http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf
homography-benchmark
homography-from-sift-features
magsac
The MAGSAC algorithm for robust model fitting without using an inlier-outlier threshold
multi-h
The C++ implementation of Multi-H algorithm, which is a multi-plane fitting technique. If you use this work for Academic purposes, please cite Barath, D. and Matas, J. and Hajder, L., Multi-H: Efficient Recovery of Tangent Planes in Stereo Images. 27th British Machine Vision Conference, 2016
pose-graph-initialization
progressive-x
The Progressive-X algorithm proposed in paper: Daniel Barath and Jiri Matas; Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm, International Conference on Computer Vision, 2019. It is available at https://arxiv.org/pdf/1906.02290
stereoglue
danini's Repositories
danini/magsac
The MAGSAC algorithm for robust model fitting without using an inlier-outlier threshold
danini/graph-cut-ransac
The Graph-Cut RANSAC algorithm proposed in paper: Daniel Barath and Jiri Matas; Graph-Cut RANSAC, Conference on Computer Vision and Pattern Recognition, 2018. It is available at http://openaccess.thecvf.com/content_cvpr_2018/papers/Barath_Graph-Cut_RANSAC_CVPR_2018_paper.pdf
danini/progressive-x
The Progressive-X algorithm proposed in paper: Daniel Barath and Jiri Matas; Progressive-X: Efficient, Anytime, Multi-Model Fitting Algorithm, International Conference on Computer Vision, 2019. It is available at https://arxiv.org/pdf/1906.02290
danini/homography-benchmark
danini/pose-graph-initialization
danini/affine-correspondences-for-camera-geometry
danini/multi-h
The C++ implementation of Multi-H algorithm, which is a multi-plane fitting technique. If you use this work for Academic purposes, please cite Barath, D. and Matas, J. and Hajder, L., Multi-H: Efficient Recovery of Tangent Planes in Stereo Images. 27th British Machine Vision Conference, 2016
danini/stereoglue
danini/homography-from-sift-features
danini/absolute-pose-from-oriented-and-scaled-features
danini/multi-x
The Multi-X algorithm proposed in paper: Daniel Barath and Jiri Matas, Multi-class model fitting by energy-minimization and mode-seeking, European Conference on Computer Vision, 2018. It is available at http://openaccess.thecvf.com/content_ECCV_2018/papers/Daniel_Barath_Multi-Class_Model_Fitting_ECCV_2018_paper.pdf
danini/five-point-fundamental
The Matlab implementation of the 5 point fundamental matrix estimator. If you use this work for Academic purposes, please cite Barath, D., Five-point fundamental matrix estimation for uncalibrated cameras, Conference on Computer Vision and Pattern Recognition, 2018
danini/clustering-in-consensus-space
danini/cvpr2022-affine-tutorial
The official site of the CVPR 2022 Affine Correspondences and Their Applications tutorial
danini/learning-good-models-in-ransac
danini/recovering-affine-features
D. Barath, "Recovering affine features from orientation-and scale-invariant ones", Asian Conference on Computer Vision (ACCV), 2019
danini/robust-line-based-estimator
danini/sutd_hololens_mapping
danini/DeepLSD
Implementation of the paper "DeepLSD: Line Segment Detection and Refinement with Deep Image Gradients"
danini/optimal-planar-motion
danini/PnP_Matlab
various PnP slover implementations in matlab, include dlt, p3p, epnp, ap3p
danini/single-affine-planar-pose
danini/stitching-with-shared-axis