Papers with Code 아카이브
Image-Based Localization
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Determining the location of an image without GPS based on cross-view matching. In most of the cases a database of satellite images is used to match the ground images to them.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/HanjiangHu/DASGIL
공식 코드DASGIL: Domain Adaptation for Semantic and Geometric-aware Image-based Localization
https://github.com/HanjiangHu/DISAM
공식 코드https://github.com/Jeff-Zilence/VIGOR
공식 코드VIGOR: Cross-View Image Geo-localization beyond One-to-one Retrieval
https://github.com/Liumouliu/deepIBL
공식 코드Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/PruneTruong/DenseMatching
공식 코드PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
https://github.com/Skyy93/Sample4Geo
공식 코드Sample4Geo: Hard Negative Sampling For Cross-View Geo-Localisation
https://github.com/gaoshuang98/cvcities
공식 코드CV-Cities: Advancing Cross-View Geo-Localization in Global Cities
https://github.com/jeff-zilence/transgeo2022
공식 코드TransGeo: Transformer Is All You Need for Cross-view Image Geo-localization
https://github.com/jonathanventura/p1ac
공식 코드P1AC: Revisiting Absolute Pose From a Single Affine Correspondence
https://github.com/layumi/University1652-Baseline
공식 코드University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization
https://github.com/shiyujiao/cross_view_localization_CVFT
공식 코드Optimal Feature Transport for Cross-View Image Geo-Localization
https://github.com/snehalbhayani/SemiGeneralizedHomography
공식 코드Calibrated and Partially Calibrated Semi-Generalized Homographies
https://github.com/tavisshore/BEV-CV
공식 코드BEV-CV: Birds-Eye-View Transform for Cross-View Geo-Localisation
https://github.com/tavisshore/SpaGBOL
공식 코드https://github.com/wentaocheng-cv/cpf_localization
공식 코드Cascaded Parallel Filtering for Memory-Efficient Image-Based Localization
https://github.com/wtyhub/LPN
공식 코드Each Part Matters: Local Patterns Facilitate Cross-view Geo-localization
https://github.com/yanghongji2007/saig
공식 코드Simple, Effective and General: A New Backbone for Cross-view Image Geo-localization
https://github.com/zhoumengjie/2-5dmap-dataset
공식 코드https://gitlab.com/jboutell/tbpos
공식 코드TBPos: Dataset for Large-Scale Precision Visual Localization
https://github.com/AggMan96/RK-Net
https://github.com/Mind23-2/MindCode-173
https://github.com/YanLiqi/HAF
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/goodproj13/DenserNet
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/layumi/AICIty-reID-2020
University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization
https://github.com/rhymesg/map_based_navigation
Aerial Map-Based Navigation Using Semantic Segmentation and Pattern Matching
https://github.com/shiyujiao/SAFA
https://github.com/yxgeee/SFRS
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
https://github.com/yxgeee/openibl
Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.