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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
Deep Image Homography EstimationCode1
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
CodingHomo: Bootstrapping Deep Homography With Video CodingCode0
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement0
HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimation0
ViewpointDepth: A New Dataset for Monocular Depth Estimation Under Viewpoint Shifts0
Semantic-aware Representation Learning for Homography EstimationCode0
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