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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Annbless/DUTCode
공식 코드DUT: Learning Video Stabilization by Simply Watching Unstable Videos
https://github.com/GrumpyZhou/patch2pix
공식 코드https://github.com/JirongZhang/DeepHomography
공식 코드https://github.com/KonstantinPakulev/BoNeSS-ST
공식 코드https://github.com/MingzhenShao/Homography_estimation
공식 코드Analyzing the Domain Shift Immunity of Deep Homography Estimation
https://github.com/NeurAI-Lab/biHomE
공식 코드Perceptual Loss for Robust Unsupervised Homography Estimation
https://github.com/Shiaoming/ALIKE
공식 코드ALIKE: Accurate and Lightweight Keypoint Detection and Descriptor Extraction
https://github.com/Shiaoming/ALIKED
공식 코드ALIKED: A Lighter Keypoint and Descriptor Extraction Network via Deformable Transformation
https://github.com/TRI-ML/KP2D
공식 코드Neural Outlier Rejection for Self-Supervised Keypoint Learning
https://github.com/aliyoussef97/silk-prp
공식 코드https://github.com/apple/ml-aspanformer
공식 코드ASpanFormer: Detector-Free Image Matching with Adaptive Span Transformer
https://github.com/arplaboratory/STHN
공식 코드STHN: Deep Homography Estimation for UAV Thermal Geo-localization with Satellite Imagery
https://github.com/arplaboratory/UASTHN
공식 코드UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localization
https://github.com/bbenligiray/stag
공식 코드https://github.com/cvg/lightglue
공식 코드https://github.com/danini/affine-correspondences-for-camera-geometry
공식 코드Making Affine Correspondences Work in Camera Geometry Computation
https://github.com/danini/graph-cut-ransac
공식 코드https://github.com/danini/homography-benchmark
공식 코드https://github.com/danini/magsac
공식 코드https://github.com/facebookresearch/silk
공식 코드https://github.com/fkluger/consac
공식 코드CONSAC: Robust Multi-Model Fitting by Conditional Sample Consensus
https://github.com/gmberton/EarthMatch
공식 코드EarthMatch: Iterative Coregistration for Fine-grained Localization of Astronaut Photography
https://github.com/imdumpl78/ihn
공식 코드https://github.com/jamycheung/matchformer
공식 코드MatchFormer: Interleaving Attention in Transformers for Feature Matching
https://github.com/junchen-yu/internet
공식 코드https://github.com/lcmhoang/hmg-dynamics
공식 코드https://github.com/liuyike422/codinghomo
공식 코드https://github.com/lu-feng/dhe-vpr
공식 코드https://github.com/lyh200095/srmatcher
공식 코드Semantic-aware Representation Learning for Homography Estimation
https://github.com/lyp-deeplearning/liftfeat
공식 코드https://github.com/magicleap/SuperPointPretrainedNetwork
공식 코드SuperPoint: Self-Supervised Interest Point Detection and Description
https://github.com/megvii-research/baseshomo
공식 코드Motion Basis Learning for Unsupervised Deep Homography Estimation with Subspace Projection
https://github.com/megvii-research/homogan
공식 코드Unsupervised Homography Estimation with Coplanarity-Aware GAN
https://github.com/megvii-research/lbhomo
공식 코드Semi-supervised Deep Large-baseline Homography Estimation with Progressive Equivalence Constraint
https://github.com/menelaoskanakis/zippypoint
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.