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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 4150 of 134 papers

TitleStatusHype
Attention Weighted Local DescriptorsCode1
Deep Image Homography EstimationCode1
MatchFormer: Interleaving Attention in Transformers for Feature MatchingCode1
Making Affine Correspondences Work in Camera Geometry ComputationCode1
3DG-STFM: 3D Geometric Guided Student-Teacher Feature MatchingCode1
MCNet: Rethinking the Core Ingredients for Accurate and Efficient Homography EstimationCode1
SCPNet: Unsupervised Cross-modal Homography Estimation via Intra-modal Self-supervised LearningCode1
Geometric Estimation via Robust Subspace RecoveryCode1
Geometrized Transformer for Self-Supervised Homography EstimationCode1
Visual SLAM with Graph-Cut Optimized Multi-Plane ReconstructionCode1
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