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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 5160 of 134 papers

TitleStatusHype
Space-Partitioning RANSACCode1
HSolo: Homography from a single affine aware correspondence0
A robust and efficient video representation for action recognition0
Deep Exposure Fusion with Deghosting via Homography Estimation and Attention Learning0
Homography Estimation with Convolutional Neural Networks Under Conditions of Variance0
Homography Estimation in Complex Topological Scenes0
Inverting RANSAC: Global Model Detection via Inlier Rate Estimation0
HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimation0
Homography Estimation From the Common Self-Polar Triangle of Separate Ellipses0
HomographyAD: Deep Anomaly Detection Using Self Homography Learning0
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