Papers with Code 아카이브

Homography Estimation

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
5
보존된 평가 기록
12

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.

평가 결과

데이터셋과 평가 조건을 선택해 성능·논문·코드를 비교하세요. 보존된 Papers with Code 기록으로, 최신 순위는 아닙니다.

S-COCO

원본 태스크: Interest Point Detection / Homography Estimation

평가 기록 5건

PDS-COCO

원본 태스크: Interest Point Detection / Homography Estimation

평가 기록 3건

Oxford and Paris

원본 태스크: Interest Point Detection / Homography Estimation

평가 기록 2건

COCO 2014

원본 태스크: Interest Point Detection / Homography Estimation

평가 기록 1건

TS-CARWC

원본 태스크: Interest Point Detection / Homography Estimation

평가 기록 1건

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.