3260 papers • 126 benchmarks • 313 datasets
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.
(Image credit: Papersgraph)
These leaderboards are used to track progress in homography-estimation-17
Use these libraries to find homography-estimation-17 models and implementations
No datasets available.
No subtasks available.
Adding a benchmark result helps the community track progress.