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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 2130 of 134 papers

TitleStatusHype
Depth-Aware Multi-Grid Deep Homography Estimation with Contextual CorrelationCode1
Geometric Estimation via Robust Subspace RecoveryCode1
ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor ExtractionCode1
CONSAC: Robust Multi-Model Fitting by Conditional Sample ConsensusCode1
Good Keypoints for the Two-View Geometry Estimation ProblemCode1
InterNet: Unsupervised Cross-modal Homography Estimation Based on Interleaved Modality Transfer and Self-supervised Homography PredictionCode1
Adapting Dense Matching for Homography Estimation with Grid-based AccelerationCode1
Deep Homography Estimation for Dynamic ScenesCode1
Attention Weighted Local DescriptorsCode1
3DG-STFM: 3D Geometric Guided Student-Teacher Feature MatchingCode1
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