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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
Semantic-aware Representation Learning for Homography EstimationCode0
SIDAR: Synthetic Image Dataset for Alignment & RestorationCode0
CodingHomo: Bootstrapping Deep Homography With Video CodingCode0
STag: A Stable Fiducial Marker SystemCode0
Towards a Unified Approach to Homography Estimation Using Image Features and Pixel IntensitiesCode0
UnsuperPoint: End-to-end Unsupervised Interest Point Detector and DescriptorCode0
Unsupervised Deep Homography: A Fast and Robust Homography Estimation ModelCode0
Video-based Sequential Bayesian Homography Estimation for Soccer Field RegistrationCode0
KP2Dtiny: Quantized Neural Keypoint Detection and Description on the EdgeCode0
Latent RANSACCode0
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