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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
Perceptual Loss for Robust Unsupervised Homography EstimationCode1
Deep Homography Estimation in Dynamic Surgical Scenes for Laparoscopic Camera Motion ExtractionCode0
Homography from two orientation- and scale-covariant featuresCode0
SIDAR: Synthetic Image Dataset for Alignment & RestorationCode0
Semantic-aware Representation Learning for Homography EstimationCode0
Rethinking Planar Homography Estimation Using Perspective FieldsCode0
Real-Time Facial Expression Emoji Masking with Convolutional Neural Networks and HomographyCode0
Content-Aware Unsupervised Deep Homography EstimationCode0
STag: A Stable Fiducial Marker SystemCode0
NeRF-Supervised Feature Point Detection and DescriptionCode0
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