Homography Estimation
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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.
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Deep Learning Reforms Image Matching: A Survey and Outlook
Words as Geometric Features: Estimating Homography using Optical Character Recognition as Compressed Image Representation
Decoupled Geometric Parameterization and its Application in Deep Homography Estimation
LiftFeat: 3D Geometry-Aware Local Feature Matching
CodingHomo: Bootstrapping Deep Homography With Video Coding
Good Keypoints for the Two-View Geometry Estimation Problem
UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localization
SeFENet: Robust Deep Homography Estimation via Semantic-Driven Feature Enhancement
Unsupervised Homography Estimation on Multimodal Image Pair via Alternating Optimization
HomoMatcher: Dense Feature Matching Results with Semi-Dense Efficiency by Homography Estimation
ViewpointDepth: A New Dataset for Monocular Depth Estimation Under Viewpoint Shifts
InterNet: Unsupervised Cross-modal Homography Estimation Based on Interleaved Modality Transfer and Self-supervised Homography Prediction
Semantic-aware Representation Learning for Homography Estimation
SCPNet: Unsupervised Cross-modal Homography Estimation via Intra-modal Self-supervised Learning
STHN: Deep Homography Estimation for UAV Thermal Geo-localization with Satellite Imagery
TP3M: Transformer-based Pseudo 3D Image Matching with Reference Image
EarthMatch: Iterative Coregistration for Fine-grained Localization of Astronaut Photography
PnLCalib: Sports Field Registration via Points and Lines Optimization
View-Centric Multi-Object Tracking with Homographic Matching in Moving UAV
NeRF-Supervised Feature Point Detection and Description
Deep Homography Estimation for Visual Place Recognition
Are Semi-Dense Detector-Free Methods Good at Matching Local Features?
Video-based Sequential Bayesian Homography Estimation for Soccer Field Registration
Automated Camera Calibration via Homography Estimation with GNNs
FMRT: Learning Accurate Feature Matching with Reconciliatory Transformer
Fine-Grained Cross-View Geo-Localization Using a Correlation-Aware Homography Estimator
Scene-Aware Feature Matching
Homography Estimation in Complex Topological Scenes
AffineGlue: Joint Matching and Robust Estimation
KP2Dtiny: Quantized Neural Keypoint Detection and Description on the Edge
LightGlue: Local Feature Matching at Light Speed
S2LD: Sparse-to-Local-Dense Matching for Geometry-Guided Correspondence Estimation
Pentagon-Match (PMatch): Identification of View-Invariant Planar Feature for Local Feature Matching-Based Homography Estimation
SIDAR: Synthetic Image Dataset for Alignment & Restoration
Analyzing the Domain Shift Immunity of Deep Homography Estimation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.