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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 6170 of 134 papers

TitleStatusHype
TP3M: Transformer-based Pseudo 3D Image Matching with Reference Image0
View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV0
NeRF-Supervised Feature Point Detection and DescriptionCode0
Are Semi-Dense Detector-Free Methods Good at Matching Local Features?0
Noisy One-point Homographies are Surprisingly Good0
Video-based Sequential Bayesian Homography Estimation for Soccer Field RegistrationCode0
Automated Camera Calibration via Homography Estimation with GNNs0
FMRT: Learning Accurate Feature Matching with Reconciliatory Transformer0
Scene-Aware Feature Matching0
Homography Estimation in Complex Topological Scenes0
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