{"id":50271,"url":"https://github.com/youkely/awesome-visual-localization","name":"awesome-visual-localization","description":"Literature review of visual localization.","projects_count":67,"last_synced_at":"2026-08-23T02:00:21.993Z","repository":{"id":44723027,"uuid":"494344931","full_name":"youkely/awesome-visual-localization","owner":"youkely","description":"Literature review of visual localization.","archived":false,"fork":false,"pushed_at":"2022-07-12T01:48:09.000Z","size":167,"stargazers_count":57,"open_issues_count":1,"forks_count":2,"subscribers_count":3,"default_branch":"main","last_synced_at":"2026-08-03T14:04:05.004Z","etag":null,"topics":["3d-vision","computer-vision","image-retrieval","pose-estimation","visual-localization"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/youkely.png","metadata":{},"created_at":"2022-05-20T06:18:52.000Z","updated_at":"2026-07-13T09:05:21.000Z","dependencies_parsed_at":"2022-09-07T01:12:31.818Z","dependency_job_id":null,"html_url":"https://github.com/youkely/awesome-visual-localization","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/youkely/awesome-visual-localization","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youkely%2Fawesome-visual-localization","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youkely%2Fawesome-visual-localization/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youkely%2Fawesome-visual-localization/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youkely%2Fawesome-visual-localization/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/youkely","download_url":"https://codeload.github.com/youkely/awesome-visual-localization/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/youkely%2Fawesome-visual-localization/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":36838870,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-08-22T15:14:58.755Z","status":"online","status_checked_at":"2026-08-23T02:00:05.822Z","response_time":128,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-14T11:15:53.799Z","updated_at":"2026-08-23T02:00:21.994Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Localization System","Localization Component","Benchmark","Challenges","Tutorial"],"sub_categories":["Scene Point Regression","Feature Match","Image Retrieval","Relative Pose Estimation","Pose Interpolation","Absolute Pose Regression","Structure-based","Structure-based With Image Retrieval","Visual Feature","Pose Computation","Structure From Motion"],"readme":"# Awesome Visual Localization: [![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nA curated list of awesome visual localization resources, inspired by [awesome-computer-vision](https://github.com/jbhuang0604/awesome-computer-vision) and [awesome-visual-localization](https://github.com/siyandong/awesome-visual-localization). Visual localization is the task to estimate the 6 dof pose of an image given a representation of the world created using a set of reference images. The representation can be a 3D reconstruction, a set of images with poses tagged or a deep neural network.\n\nThis document might have some errors or missing parts. Feel free to make suggestions or pull request. All contributions are well appreciated.\n\n## Table of Contents\n\n- [Main challenges](#main-challenges)\n- [Benchmark](#benchmark)\n- [Challenges](#challenges)\n- [Tutorial](#tutorial)\n- [Category](#category)\n- [Localization Component](#localization-component)\n    - [Visual Feature](#visual-feature)\n    - [Image Retrieval](#image-retrieval)\n    - [Feature Match](#feature-match)\n    - [Pose Computation](#pose-computation)\n    - [Structure From Motion](#structure-from-motion)\n- [Localization System](#localization-system)\n    - [Structure-based](structure-based)\n    - [Structure-based With Image Retrieval](#structure-based-with-image-retrieval)\n    - [Scene Point Regression](#scene-point-regression)\n    - [Absolute Pose Regression](#absolute-pose-regression)\n    - [Pose Interpolation](#pose-interpolation)\n    - [Relative Pose Estimation](#relative-pose-estimation)\n\n\n## Main Challenges\n- Illumination changes\n- Dynamic scenes with moving objects\n- Long-time period with different seasons\n- Occlusion of the scene by an object or person\n- Strong viewpoint difference\n\n## Benchmark\n- [LONG-TERM VISUAL LOCALIZATION](https://www.visuallocalization.net/)\n\n## Challenges\n- [2022 ECCV] [Map-Based Localization for Autonomous Driving](https://www.sites.google.com/view/mlad-eccv2022)\n- [2021 ICCV] [Long-Term Visual Localization under Changing Conditions](https://sites.google.com/view/ltvl2021/home)\n- [2021 ICCV] [Map-Based Localization for Autonomous Driving](https://sites.google.com/view/mlad-iccv2021)\n- [2020 ECCV] [Long-Term Visual Localization under Changing Conditions](https://www.visuallocalization.net/workshop/eccv/2020/)\n- [2020 ECCV] [Map-Based Localization for Autonomous Driving](https://sites.google.com/view/mlad-eccv2020/home)\n- [2019 CVPR] [Long-Term Visual Localization under Changing Conditions](https://sites.google.com/view/ltvl2019/home)\n\n## Tutorial\n- [ICCV 2021 Large-Scale Visual Localization](https://sites.google.com/view/lsvpr2021/home)\n\n## Category\n|               Approach               | 3D map |                              Pros                              |                                                          Cons                                                         |\n|:------------------------------------:|:------:|:--------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------------------:|\n| Structure-based                      | yes    | Perform very well in most scenarios                            | Challenging in large environments in terms of processing time and memory consumption                                  |\n| Structure-based with image retrieval | yes    | Improve speed and robustness for large-scale settings          | Quality heavily relies on image retrieval                                                                             |\n| Scene point regression               | yes/no | Very accurate position in small-scale settings                 | To be improved in large environments                                                                                  |\n| Absolute pose regression             | no     | Fast pose approximation, can be trained for certain challenges | Low accuracy                                                                                                          |\n| Pose interpolation                   | no     | Fast and lightweight                                           | Quality relies heavily on image retrieval and only provides a rough pose                                              |\n| Relative pose estimation             | no     | Fast and lightweight                                           | Quality relies heavily on image retrieval and, e.g., local feature matches or a DNN used for relative pose estimation |\n\n\n\u003cbr/\u003e\u003cbr/\u003e\u003cbr/\u003e\n\u003cimg src=\"https://europe.naverlabs.com/wp-content/uploads/2021/03/visual_localization_methods.png\" width=\"800px\"\u003e\n\u003cbr/\u003e\nImage from https://europe.naverlabs.com/blog/methods-for-visual-localization/\n\n\n\n\n## Localization Component\n\n### Visual Feature\n- [2020 CVPR] ASLFeat: Learning Local Features of Accurate Shape and Localization [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Luo_ASLFeat_Learning_Local_Features_of_Accurate_Shape_and_Localization_CVPR_2020_paper.pdf)\n- [2020 ECCV] Learning Feature Descriptors Using Camera Pose Supervision [[paper]](https://arxiv.org/pdf/2004.13324.pdf?ref=https://githubhelp.com)\n- [2019 NeurIPS] R2D2: Reliable and Repeatable Detector and Descriptor [[paper]](https://proceedings.neurips.cc/paper/2019/file/3198dfd0aef271d22f7bcddd6f12f5cb-Paper.pdf)\n- [2019 CVPR] D2-Net: A Trainable CNN for Joint Description and Detection of Local Features [[paper]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Dusmanu_D2-Net_A_Trainable_CNN_for_Joint_Description_and_Detection_of_CVPR_2019_paper.pdf)\n- [2019 arXiv] From handcrafted to deep local features [[paper]](https://arxiv.org/pdf/1807.10254)\n- [2018 CVPR] Semantic Visual Localization [[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Schonberger_Semantic_Visual_Localization_CVPR_2018_paper.pdf)\n- [2018 CVPR] SuperPoint: Self-Supervised Interest Point Detection and Description [[paper]](https://openaccess.thecvf.com/content_cvpr_2018_workshops/papers/w9/DeTone_SuperPoint_Self-Supervised_Interest_CVPR_2018_paper.pdf)\n- [2017 CVPR] Comparative Evaluation of Hand-Crafted and Learned Local Features [[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Schonberger_Comparative_Evaluation_of_CVPR_2017_paper.pdf)\n- [2017 ICRA] Semantics-aware visual localization under challenging perceptual conditions [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=7989305\u0026ref=aHR0cHM6Ly9zY2hvbGFyLmdvb2dsZS5jby5qcC8=)\n- [2004 IJCV] Distinctive Image Features from Scale-Invariant Keypoints [[paper]](https://link.springer.com/content/pdf/10.1023/B:VISI.0000029664.99615.94.pdf)\n\n### Image Retrieval\n- [2022 arXiv] Investigating the Role of Image Retrieval for Visual Localization -- An exhaustive benchmark [[paper]](https://arxiv.org/pdf/2205.15761)\n- [2019 ICCV] Learning With Average Precision: Training Image Retrieval With a Listwise Loss [[paper]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Revaud_Learning_With_Average_Precision_Training_Image_Retrieval_With_a_Listwise_ICCV_2019_paper.pdf)\n- [2019 TPAMI] Fine-Tuning CNN Image Retrieval with No Human Annotation [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=8382272\u0026ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2Fic3RyYWN0L2RvY3VtZW50LzgzODIyNzI/Y2FzYV90b2tlbj1zMnlndGdkLUpYMEFBQUFBOmgtMm9Kb1NLT1dQZmZoMUlwRFJwTnVBbnVsUGhYLTRoNHVpNnlVMWY5VmZPOXgzMU05M1p6Y0pIcUo4aVNjVFJYcmlTREQybkkwT0NJTlE=)\n- [2017 IJCV] End-to-End Learning of Deep Visual Representations for Image Retrieval [[paper]](https://link.springer.com/content/pdf/10.1007/s11263-017-1016-8.pdf)\n- [2016 CVPR] NetVLAD: CNN Architecture for Weakly Supervised Place Recognition [[paper]](https://openaccess.thecvf.com/content_cvpr_2016/papers/Arandjelovic_NetVLAD_CNN_Architecture_CVPR_2016_paper.pdf)\n- [2015 CVPR] 24/7 Place Recognition by View Synthesis [[paper]](https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Torii_247_Place_Recognition_2015_CVPR_paper.pdf)\n\n### Feature Match\n- [2022 arXiv] Is Geometry Enough for Matching in Visual Localization? [[paper]](https://arxiv.org/pdf/2203.12979)\n- [2021 CVPR] LoFTR: Detector-Free Local Feature Matching with Transformers [[paper]](https://arxiv.org/pdf/2104.00680.pdf) [[code]](https://github.com/zju3dv/LoFTR) [[project]](https://zju3dv.github.io/loftr/)\n- [2020 ECCV] S2DNet : Learning Image Features for Accurate Sparse-to-Dense Matching [[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123480630.pdf) [[code]](https://github.com/germain-hug/S2DNet-Minimal)\n- [2020 CVPR] SuperGlue: Learning Feature Matching With Graph Neural Networks [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Sarlin_SuperGlue_Learning_Feature_Matching_With_Graph_Neural_Networks_CVPR_2020_paper.pdf)\n- [2019 3DV] Sparse-to-Dense Hypercolumn Matching for Long-Term Visual Localization [[paper]](https://arxiv.org/pdf/1907.03965) [[code]](https://github.com/germain-hug/S2DHM)\n- [2018 ECCV] Semantic Match Consistency for Long-Term Visual Localization [[paper]](https://openaccess.thecvf.com/content_ECCV_2018/papers/Carl_Toft_Semantic_Match_Consistency_ECCV_2018_paper.pdf)\n- [2017 TPAMI] Efficient amp; Effective Prioritized Matching for Large-Scale Image-Based Localization [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=7572201\u0026ref=aHR0cHM6Ly9zY2hvbGFyLmdvb2dsZS5jby5qcC8=)\n- [2017 ICCV] Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=8237522\u0026ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2RvY3VtZW50LzgyMzc1MjI=)\n- [2014 3DV] Matching Features Correctly through Semantic Understanding [[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\u0026arnumber=7035860)\n- [2008 TPAMI] Optimal Randomized RANSAC [[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=\u0026arnumber=4359381)\n- [1981 CACM] Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography [[paper]](https://dl.acm.org/doi/pdf/10.1145/358669.358692)\n\n### Pose Computation\n- [2022 CVPR] The Probabilistic Normal Epipolar Constraint for Frame-To-Frame Rotation Optimization under Uncertain Feature Positions [[paper]](https://openaccess.thecvf.com/content/CVPR2022/papers/Muhle_The_Probabilistic_Normal_Epipolar_Constraint_for_Frame-to-Frame_Rotation_Optimization_Under_CVPR_2022_paper.pdf)\n- [2020 ECCV] Solving the Blind Perspective-n-Point Problem End-To-End With Robust Differentiable Geometric Optimization [[paper]](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123470239.pdf) [[code]](https://github.com/dylan-campbell/bpnpnet)\n- [2011 CVPR] A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=5995464\u0026ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2RvY3VtZW50LzU5OTU0NjQ=)\n\n### Structure From Motion\n- [2016 CVPR] Structure-from-Motion Revisited [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=7780814\u0026ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2RvY3VtZW50Lzc3ODA4MTQ=)\n- [2013 ICCV] Global Fusion of Relative Motions for Robust, Accurate and Scalable Structure from Motion [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=6751515\u0026ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2RvY3VtZW50LzY3NTE1MTU=)\n\n## Localization System\n\n### Structure-based\n- [2021 CVPR] Back to the Feature: Learning Robust Camera Localization from Pixels to Pose [[paper]](https://openaccess.thecvf.com/content/CVPR2021/papers/Sarlin_Back_to_the_Feature_Learning_Robust_Camera_Localization_From_Pixels_CVPR_2021_paper.pdf) [[code]](https://github.com/cvg/pixloc)\n- [2019 CVPR] Visual Localization by Learning Objects-Of-Interest Dense Match Regression [[paper]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Weinzaepfel_Visual_Localization_by_Learning_Objects-Of-Interest_Dense_Match_Regression_CVPR_2019_paper.pdf)\n- [2018 CVPR] InLoc: Indoor Visual Localization with Dense Matching and View Synthesis [[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Taira_InLoc_Indoor_Visual_CVPR_2018_paper.pdf) [[code]](https://github.com/HajimeTaira/InLoc_demo)\n- [2011 ICCV] Fast Image-Based Localization using Direct 2D-to-3D Matching [[paper]](https://www.graphics.rwth-aachen.de/media/papers/sattler_iccv11_preprint_011.pdf)\n\n### Structure-based With Image Retrieval\n- [2022 arXiv] Robust Image Retrieval-based Visual Localization using Kapture [[paper]](https://arxiv.org/pdf/2007.13867.pdf) [[code]](https://github.com/naver/kapture-localization)\n- [2020 ECCV Workshop] Hierarchical Localization with hloc and SuperGlue [[slides]](https://psarlin.com/assets/talks/hloc+SuperGlue_15min_ltvl_slides.pdf) [[code]](https://github.com/cvg/Hierarchical-Localization)\n- [2019 CVPR] From Coarse to Fine: Robust Hierarchical Localization at Large Scale [[paper]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Sarlin_From_Coarse_to_Fine_Robust_Hierarchical_Localization_at_Large_Scale_CVPR_2019_paper.pdf) [[code]](https://github.com/ethz-asl/hfnet)\n\n### Scene Point Regression\n- [2021 TPAMI] Visual Camera Re-Localization from RGB and RGB-D Images Using DSAC [[paper]](https://arxiv.org/pdf/2002.12324.pdf) [[code]](https://github.com/vislearn/dsacstar)\n- [2020 CVPR] Hierarchical Scene Coordinate Classification and Regression for Visual Localization [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_Hierarchical_Scene_Coordinate_Classification_and_Regression_for_Visual_Localization_CVPR_2020_paper.pdf) [[code]](https://github.com/AaltoVision/hscnet)\n- [2019 ICCV] SANet: Scene Agnostic Network for Camera Localization [[paper]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Yang_SANet_Scene_Agnostic_Network_for_Camera_Localization_ICCV_2019_paper.pdf) [[code]](https://github.com/sfu-gruvi-3dv/sanet_relocal_demo)\n- [2019 ICCV] Expert Sample Consensus Applied to Camera Re-Localization [[paper]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Brachmann_Expert_Sample_Consensus_Applied_to_Camera_Re-Localization_ICCV_2019_paper.pdf) [[code]](https://github.com/vislearn/esac)\n- [2018 CVPR] Learning Less is More – 6D Camera Localization via 3D Surface Regression [[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Brachmann_Learning_Less_Is_CVPR_2018_paper.pdf) [[code]](https://github.com/vislearn/LessMore)\n- [2017 CVPR] DSAC - Differentiable RANSAC for Camera Localization [[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Brachmann_DSAC_-_Differentiable_CVPR_2017_paper.pdf) [[code]](https://github.com/cvlab-dresden/DSAC)\n- [2013 CVPR] Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images [[paper]](https://openaccess.thecvf.com/content_cvpr_2013/papers/Shotton_Scene_Coordinate_Regression_2013_CVPR_paper.pdf)\n\n### Absolute Pose Regression\n- [2018 ICRA] Deep Auxiliary Learning for Visual Localization and Odometry [[paper]](https://arxiv.org/pdf/1803.03642.pdf)\n- [2018 RA-L] VLocNet++: Deep Multitask Learning for Semantic Visual Localization and Odometry [[paper]](https://arxiv.org/pdf/1804.08366.pdf)\n- [2018 CVPR] Geometry-Aware Learning of Maps for Camera Localization [[paper]](https://openaccess.thecvf.com/content_cvpr_2018/papers/Brahmbhatt_Geometry-Aware_Learning_of_CVPR_2018_paper.pdf) [[code]](https://github.com/NVlabs/geomapnet)\n- [2017 CVPR] Image-based localization using LSTMs for structured feature correlation [[paper]](https://openaccess.thecvf.com/content_ICCV_2017/papers/Walch_Image-Based_Localization_Using_ICCV_2017_paper.pdf)\n- [2017 CVPR] Geometric loss functions for camera pose regression with deep learning [[paper]](https://openaccess.thecvf.com/content_cvpr_2017/papers/Kendall_Geometric_Loss_Functions_CVPR_2017_paper.pdf)\n- [2015 ICCV] PoseNet: A Convolutional Network for Real-Time 6-DOF Camera Relocalization [[paper]](https://openaccess.thecvf.com/content_iccv_2015/papers/Kendall_PoseNet_A_Convolutional_ICCV_2015_paper.pdf)\n\n### Pose Interpolation\n- [2019 CVPR] Understanding the Limitations of CNN-based Absolute Camera Pose Regression [[paper]](https://openaccess.thecvf.com/content_CVPR_2019/papers/Sattler_Understanding_the_Limitations_of_CNN-Based_Absolute_Camera_Pose_Regression_CVPR_2019_paper.pdf)\n- [2011 ICCV Workshop] Visual localization by linear combination of image descriptors [[paper]](https://ieeexplore.ieee.org/stampPDF/getPDF.jsp?tp=\u0026arnumber=6130230\u0026ref=aHR0cHM6Ly9pZWVleHBsb3JlLmllZWUub3JnL2RvY3VtZW50LzYxMzAyMzA=)\n\n### Relative Pose Estimation\n- [2020 ICRA] To Learn or Not to Learn: Visual Localization from Essential Matrices [[paper]](https://arxiv.org/pdf/1908.01293.pdf)\n- [2019 ICCV] CamNet: Coarse-to-Fine Retrieval for Camera Re-Localization [[paper]](https://openaccess.thecvf.com/content_ICCV_2019/papers/Ding_CamNet_Coarse-to-Fine_Retrieval_for_Camera_Re-Localization_ICCV_2019_paper.pdf)\n- [2018 ECCV] RelocNet: Continuous Metric Learning Relocalisation using Neural Nets [[paper]](https://openaccess.thecvf.com/content_ECCV_2018/papers/Vassileios_Balntas_RelocNet_Continous_Metric_ECCV_2018_paper.pdf) \n- [2017 ICCV Workshop] Camera Relocalization by Computing Pairwise Relative Poses Using Convolutional Neural Network [[paper]](https://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w17/Laskar_Camera_Relocalization_by_ICCV_2017_paper.pdf) [[code]](https://github.com/AaltoVision/camera-relocalisation)\n- [2006 3DPVT] Image Based Localization in Urban Environments [[paper]](https://web.archive.org/web/20130512063647id_/http://www.cs.gmu.edu:80/~wzhang2/publication/Localization1.pdf)\n\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/youkely%2Fawesome-visual-localization/projects"}