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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 121130 of 134 papers

TitleStatusHype
PRISE: Demystifying Deep Lucas-Kanade with Strongly Star-Convex Constraints for Multimodel Image Alignment0
Radial Distortion Homography0
Road-aware Monocular Structure from Motion and Homography Estimation0
Robust Homography Estimation via Dual Principal Component Pursuit0
Robust Multiple Homography Estimation: An Ill-Solved Problem0
Scene-Aware Feature Matching0
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement0
SiLK: Simple Learned Keypoints0
SSORN: Self-Supervised Outlier Removal Network for Robust Homography Estimation0
SWIGS: A Swift Guided Sampling Method0
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