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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 8190 of 134 papers

TitleStatusHype
Full explicit consistency constraints in uncalibrated multiple homography estimation0
G2MF-WA: Geometric Multi-Model Fitting with Weakly Annotated Data0
Galois/monodromy groups for decomposing minimal problems in 3D reconstruction0
Generative Adversarial Frontal View to Bird View Synthesis0
Geometric Multi-Model Fitting with a Convex Relaxation Algorithm0
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
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