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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 101110 of 134 papers

TitleStatusHype
ParaFormer: Parallel Attention Transformer for Efficient Feature Matching0
Pentagon-Match (PMatch): Identification of View-Invariant Planar Feature for Local Feature Matching-Based Homography Estimation0
Pixel-wise Deep Image Stitching0
Planar Object Tracking in the Wild: A Benchmark0
Precise Aerial Image Matching based on Deep Homography Estimation0
PRISE: Demystifying Deep Lucas-Kanade with Strongly Star-Convex Constraints for Multimodel Image Alignment0
Radial Distortion Homography0
SiLK: Simple Learned Keypoints0
SSORN: Self-Supervised Outlier Removal Network for Robust Homography Estimation0
SWIGS: A Swift Guided Sampling Method0
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