Homography Estimation

30 papers with code • 4 benchmarks • 7 datasets

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Most implemented papers

SuperPoint: Self-Supervised Interest Point Detection and Description

magicleap/SuperGluePretrainedNetwork 20 Dec 2017

This paper presents a self-supervised framework for training interest point detectors and descriptors suitable for a large number of multiple-view geometry problems in computer vision.

Deep Image Homography Estimation

JirongZhang/DeepHomography 13 Jun 2016

We present a deep convolutional neural network for estimating the relative homography between a pair of images.

Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model

tynguyen/unsupervisedDeepHomographyRAL2018 12 Sep 2017

Homography estimation between multiple aerial images can provide relative pose estimation for collaborative autonomous exploration and monitoring.

CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus

fkluger/consac CVPR 2020

We present a robust estimator for fitting multiple parametric models of the same form to noisy measurements.

MAGSAC: marginalizing sample consensus

danini/magsac CVPR 2019

A method called, sigma-consensus, is proposed to eliminate the need for a user-defined inlier-outlier threshold in RANSAC.

UnsuperPoint: End-to-end Unsupervised Interest Point Detector and Descriptor

791136190/UnsuperPoint_PyTorch 9 Jul 2019

In this work, we introduce an unsupervised deep learning-based interest point detector and descriptor.

Neural Outlier Rejection for Self-Supervised Keypoint Learning


By making the sampling of inlier-outlier sets from point-pair correspondences fully differentiable within the keypoint learning framework, we show that are able to simultaneously self-supervise keypoint description and improve keypoint matching.

STag: A Stable Fiducial Marker System

bbenligiray/stag 19 Jul 2017

Jitter impairs robustness in vision and robotics applications, and deteriorates the sense of presence and immersion in AR/VR applications.


rlit/LatentRANSAC CVPR 2018

We present a method that can evaluate a RANSAC hypothesis in constant time, i. e. independent of the size of the data.

Optimal Multi-view Correction of Local Affine Frames

eivan/multiview-LAFs-correction 1 May 2019

The technique requires the epipolar geometry to be pre-estimated between each image pair.