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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

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Showing 51–75 of 134 papers

TitleStatusHype
UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localizationCode1
Road-aware Monocular Structure from Motion and Homography Estimation—0
Robust Homography Estimation via Dual Principal Component Pursuit—0
Robust Multiple Homography Estimation: An Ill-Solved Problem—0
Scene-Aware Feature Matching—0
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement—0
STN-Homography: estimate homography parameters directly—0
AbHE: All Attention-based Homography Estimation—0
AffineGlue: Joint Matching and Robust Estimation—0
A Large-Scale Homography Benchmark—0
ViewpointDepth: A New Dataset for Monocular Depth Estimation Under Viewpoint Shifts—0
Are Semi-Dense Detector-Free Methods Good at Matching Local Features?—0
A Robust and Efficient Framework for Sports-Field Registration—0
A robust and efficient video representation for action recognition—0
Automated Camera Calibration via Homography Estimation with GNNs—0
Automated Top View Registration of Broadcast Football Videos—0
Camera Intrinsic Blur Kernel Estimation: A Reliable Framework—0
Character Keypoint-based Homography Estimation in Scanned Documents for Efficient Information Extraction—0
CLKN: Cascaded Lucas-Kanade Networks for Image Alignment—0
Coding local and global binary visual features extracted from video sequences—0
Co-Attention for Conditioned Image Matching—0
Decoupled Geometric Parameterization and its Application in Deep Homography Estimation—0
Deep Exposure Fusion with Deghosting via Homography Estimation and Attention Learning—0
Deep Learning Reforms Image Matching: A Survey and Outlook—0
DeepMeshFlow: Content Adaptive Mesh Deformation for Robust Image Registration—0
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