SOTAVerified

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 121130 of 134 papers

TitleStatusHype
Towards a Unified Approach to Homography Estimation Using Image Features and Pixel IntensitiesCode0
CodingHomo: Bootstrapping Deep Homography With Video CodingCode0
KP2Dtiny: Quantized Neural Keypoint Detection and Description on the EdgeCode0
UnsuperPoint: End-to-end Unsupervised Interest Point Detector and DescriptorCode0
Unsupervised Deep Homography: A Fast and Robust Homography Estimation ModelCode0
Homography from two orientation- and scale-covariant featuresCode0
Deep Homography Estimation in Dynamic Surgical Scenes for Laparoscopic Camera Motion ExtractionCode0
Semantic-aware Representation Learning for Homography EstimationCode0
Rethinking Planar Homography Estimation Using Perspective FieldsCode0
SIDAR: Synthetic Image Dataset for Alignment & RestorationCode0
Show:102550
← PrevPage 13 of 14Next →

No leaderboard results yet.