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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
Making Affine Correspondences Work in Camera Geometry ComputationCode1
MatchFormer: Interleaving Attention in Transformers for Feature MatchingCode1
InterNet: Unsupervised Cross-modal Homography Estimation Based on Interleaved Modality Transfer and Self-supervised Homography PredictionCode1
Online Invariance Selection for Local Feature DescriptorsCode1
Perceptual Loss for Robust Unsupervised Homography EstimationCode1
Recurrent Homography Estimation Using Homography-Guided Image Warping and Focus TransformerCode1
Line as a Visual Sentence: Context-aware Line Descriptor for Visual LocalizationCode1
SEKD: Self-Evolving Keypoint Detection and DescriptionCode1
Geometrized Transformer for Self-Supervised Homography EstimationCode1
Visual SLAM with Graph-Cut Optimized Multi-Plane ReconstructionCode1
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