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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 110 of 134 papers

TitleStatusHype
HomographyAD: Deep Anomaly Detection Using Self Homography Learning0
Deep Learning Reforms Image Matching: A Survey and Outlook0
Words as Geometric Features: Estimating Homography using Optical Character Recognition as Compressed Image Representation0
Decoupled Geometric Parameterization and its Application in Deep Homography Estimation0
LiftFeat: 3D Geometry-Aware Local Feature MatchingCode3
CodingHomo: Bootstrapping Deep Homography With Video CodingCode0
Good Keypoints for the Two-View Geometry Estimation ProblemCode1
UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localizationCode1
Adapting Dense Matching for Homography Estimation with Grid-based AccelerationCode1
SSHNet: Unsupervised Cross-modal Homography Estimation via Problem Reformulation and Split OptimizationCode1
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