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Homography Estimation

Homography estimation is a technique used in computer vision and image processing to find the relationship between two images of the same scene, but captured from different viewpoints. It is used to align images, correct for perspective distortions, or perform image stitching. In order to estimate the homography, a set of corresponding points between the two images must be found, and a mathematical model must be fit to these points. There are various algorithms and techniques that can be used to perform homography estimation, including direct methods, RANSAC, and machine learning-based approaches.

Papers

Showing 101110 of 134 papers

TitleStatusHype
GPO: Global Plane Optimization for Fast and Accurate Monocular SLAM Initialization0
GyroFlow+: Gyroscope-Guided Unsupervised Deep Homography and Optical Flow Learning0
HomographyAD: Deep Anomaly Detection Using Self Homography Learning0
Homography Estimation From the Common Self-Polar Triangle of Separate Ellipses0
Homography Estimation in Complex Topological Scenes0
Homography Estimation with Convolutional Neural Networks Under Conditions of Variance0
HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimation0
HSolo: Homography from a single affine aware correspondence0
Insights into the robustness of control point configurations for homography and planar pose estimation0
Inverting RANSAC: Global Model Detection via Inlier Rate Estimation0
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