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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 126134 of 134 papers

TitleStatusHype
Scene-Aware Feature Matching0
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement0
SiLK: Simple Learned Keypoints0
SSORN: Self-Supervised Outlier Removal Network for Robust Homography Estimation0
SWIGS: A Swift Guided Sampling Method0
TP3M: Transformer-based Pseudo 3D Image Matching with Reference Image0
View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV0
Warped Convolutional Networks: Bridge Homography to sl(3) algebra by Group Convolution0
Words as Geometric Features: Estimating Homography using Optical Character Recognition as Compressed Image Representation0
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