{"url":"/task/geo-localization","name":"geo-localization","slug":"geo-localization","description_markdown":null,"categories":[{"name":"Computer Vision","url":"/area/computer-vision"}],"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","slug_source":"archive_url"},"counts":{"papers_tagged":140,"papers_with_code":76,"benchmarks":0,"benchmark_tables_in_archive":0,"benchmark_tables_shown":0,"benchmark_tables_withheld_as_spam":0,"benchmark_definition":"a leaderboard table with at least one row; benchmark_tables_shown also counts the zero-row tables; benchmark_tables_in_archive adds the tables withheld as spam","datasets":8,"subtasks":0,"parent_tasks":1},"benchmarks":[],"datasets":[{"url":"/dataset/university-1652","name":"University-1652","full_name":"","num_papers_in_archive":19},{"url":"/dataset/shipsg","name":"ShipSG","full_name":"Ship Segmentation and Georeferencing Dataset","num_papers_in_archive":6},{"url":"/dataset/cv-cities","name":"CV-Cities","full_name":"","num_papers_in_archive":3},{"url":"/dataset/spagbol","name":"SpaGBOL","full_name":"Spatial-Graph-Based Orientated Cross-View Geo-Localisation","num_papers_in_archive":3},{"url":"/dataset/denseuav","name":"DenseUAV","full_name":"","num_papers_in_archive":2},{"url":"/dataset/gta-uav","name":"GTA-UAV","full_name":"","num_papers_in_archive":1},{"url":"/dataset/pdfm-embeddings","name":"PDFM Embeddings","full_name":"Population Dynamics Foundation Model Embeddings","num_papers_in_archive":1},{"url":"/dataset/peng","name":"PEnG","full_name":"Pose-Enhanced Geo-Localisation","num_papers_in_archive":1}],"subtasks":[],"parent_tasks":[{"url":"/task/visual-place-recognition","name":"Visual Place Recognition"}],"papers":{"order":"repositories listed in the archive (desc), then date (desc); the archive holds no stars","population":"papers tagged with this task that list at least one repository in the archive","shown":30,"of":76,"tagged_in_all":140,"items":[{"url":"/paper/mobilenets-efficient-convolutional-neural","title":"MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications","date":"2017-04-17","arxiv_id":"1704.04861","repositories_listed":159,"syntology":{"n":83,"n_ran":52,"n_unverified":31,"n_pointer_only":48}},{"url":"/paper/learning-transferable-visual-models-from","title":"Learning Transferable Visual Models From Natural Language Supervision","date":"2021-02-26","arxiv_id":"2103.00020","repositories_listed":82,"syntology":{"n":20,"n_ran":16,"n_unverified":4,"n_pointer_only":16}},{"url":"/paper/smdt-cross-view-geo-localization-with-image","title":"SMDT: Cross-View Geo-Localization with Image Alignment and Transformer","date":"2022-04-06","arxiv_id":null,"repositories_listed":4,"syntology":null},{"url":"/paper/geoclip-clip-inspired-alignment-between","title":"GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization","date":"2023-09-27","arxiv_id":"2309.16020","repositories_listed":3,"syntology":{"n":13,"n_ran":5,"n_unverified":8,"n_pointer_only":0}},{"url":"/paper/university-1652-a-multi-view-multi-source","title":"University-1652: A Multi-view Multi-source Benchmark for Drone-based Geo-localization","date":"2020-02-27","arxiv_id":"2002.12186","repositories_listed":3,"syntology":{"n":15,"n_ran":1,"n_unverified":14,"n_pointer_only":0}},{"url":"/paper/cross-view-geo-localization-with-street-view","title":"Cross-View Geo-Localization with Street-View and VHR Satellite Imagery in Decentrality Settings","date":"2024-12-16","arxiv_id":"2412.11529","repositories_listed":2,"syntology":null},{"url":"/paper/cross-view-meets-diffusion-aerial-image","title":"Cross-View Meets Diffusion: Aerial Image Synthesis with Geometry and Text Guidance","date":"2024-08-08","arxiv_id":"2408.04224","repositories_listed":2,"syntology":null},{"url":"/paper/gomaa-geo-goal-modality-agnostic-active-geo","title":"GOMAA-Geo: GOal Modality Agnostic Active Geo-localization","date":"2024-06-04","arxiv_id":"2406.01917","repositories_listed":2,"syntology":{"n":7,"n_ran":5,"n_unverified":2,"n_pointer_only":0}},{"url":"/paper/a-semantic-segmentation-guided-approach-for","title":"A Semantic Segmentation-guided Approach for Ground-to-Aerial Image Matching","date":"2024-04-17","arxiv_id":"2404.11302","repositories_listed":2,"syntology":null},{"url":"/paper/towards-natural-language-guided-drones","title":"Towards Natural Language-Guided Drones: GeoText-1652 Benchmark with Spatial Relation Matching","date":"2023-11-21","arxiv_id":"2311.12751","repositories_listed":2,"syntology":null},{"url":"/paper/long-range-uav-thermal-geo-localization-with","title":"Long-range UAV Thermal Geo-localization with Satellite Imagery","date":"2023-06-05","arxiv_id":"2306.02994","repositories_listed":2,"syntology":{"n":6,"n_ran":4,"n_unverified":2,"n_pointer_only":0}},{"url":"/paper/multiple-environment-self-adaptive-network","title":"Multiple-environment Self-adaptive Network for Aerial-view Geo-localization","date":"2022-04-18","arxiv_id":"2204.08381","repositories_listed":2,"syntology":{"n":7,"n_ran":3,"n_unverified":4,"n_pointer_only":0}},{"url":"/paper/rethinking-visual-geo-localization-for-large","title":"Rethinking Visual Geo-localization for Large-Scale Applications","date":"2022-04-05","arxiv_id":"2204.02287","repositories_listed":2,"syntology":{"n":10,"n_ran":6,"n_unverified":4,"n_pointer_only":2}},{"url":"/paper/gre-suite-geo-localization-inference-via-fine","title":"GRE Suite: Geo-localization Inference via Fine-Tuned Vision-Language Models and Enhanced Reasoning Chains","date":"2025-05-24","arxiv_id":"2505.18700","repositories_listed":1,"syntology":null},{"url":"/paper/object-level-cross-view-geo-localization-with","title":"Object-level Cross-view Geo-localization with Location Enhancement and Multi-Head Cross Attention","date":"2025-05-23","arxiv_id":"2505.17911","repositories_listed":1,"syntology":null},{"url":"/paper/geolocating-earth-imagery-from-iss","title":"Geolocating Earth Imagery from ISS: Integrating Machine Learning with Astronaut Photography for Enhanced Geographic Mapping","date":"2025-04-29","arxiv_id":"2504.21194","repositories_listed":1,"syntology":null},{"url":"/paper/scale-efficient-training-for-large-datasets-1","title":"Scale Efficient Training for Large Datasets","date":"2025-03-17","arxiv_id":"2503.13385","repositories_listed":1,"syntology":{"n":6,"n_ran":3,"n_unverified":3,"n_pointer_only":6}},{"url":"/paper/navig-natural-language-guided-analysis-with","title":"NAVIG: Natural Language-guided Analysis with Vision Language Models for Image Geo-localization","date":"2025-02-20","arxiv_id":"2502.14638","repositories_listed":1,"syntology":null},{"url":"/paper/without-paired-labeled-data-an-end-to-end","title":"Without Paired Labeled Data: An End-to-End Self-Supervised Paradigm for UAV-View Geo-Localization","date":"2025-02-17","arxiv_id":"2502.11381","repositories_listed":1,"syntology":null},{"url":"/paper/uasthn-uncertainty-aware-deep-homography","title":"UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localization","date":"2025-02-03","arxiv_id":"2502.01035","repositories_listed":1,"syntology":{"n":8,"n_ran":7,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/where-am-i-cross-view-geo-localization-with","title":"Where am I? Cross-View Geo-localization with Natural Language Descriptions","date":"2024-12-22","arxiv_id":"2412.17007","repositories_listed":1,"syntology":null},{"url":"/paper/multi-level-embedding-and-alignment-network","title":"Multi-Level Embedding and Alignment Network with Consistency and Invariance Learning for Cross-View Geo-Localization","date":"2024-12-19","arxiv_id":"2412.14819","repositories_listed":1,"syntology":null},{"url":"/paper/sf-loc-a-visual-mapping-and-geo-localization","title":"SF-Loc: A Visual Mapping and Geo-Localization System based on Sparse Visual Structure Frames","date":"2024-12-02","arxiv_id":"2412.01500","repositories_listed":1,"syntology":null},{"url":"/paper/peng-pose-enhanced-geo-localisation","title":"PEnG: Pose-Enhanced Geo-Localisation","date":"2024-11-24","arxiv_id":"2411.15742","repositories_listed":1,"syntology":null},{"url":"/paper/video2bev-transforming-drone-videos-to-bevs","title":"Video2BEV: Transforming Drone Videos to BEVs for Video-based Geo-localization","date":"2024-11-20","arxiv_id":"2411.13610","repositories_listed":1,"syntology":null},{"url":"/paper/cv-cities-advancing-cross-view-geo","title":"CV-Cities: Advancing Cross-View Geo-Localization in Global Cities","date":"2024-11-19","arxiv_id":"2411.12431","repositories_listed":1,"syntology":{"n":9,"n_ran":0,"n_unverified":9,"n_pointer_only":0}},{"url":"/paper/cityguessr-city-level-video-geo-localization","title":"CityGuessr: City-Level Video Geo-Localization on a Global Scale","date":"2024-11-10","arxiv_id":"2411.06344","repositories_listed":1,"syntology":{"n":2,"n_ran":0,"n_unverified":2,"n_pointer_only":2}},{"url":"/paper/advanced-computer-vision-for-extracting","title":"Advanced computer vision for extracting georeferenced vehicle trajectories from drone imagery","date":"2024-11-04","arxiv_id":"2411.02136","repositories_listed":1,"syntology":null},{"url":"/paper/game4loc-a-uav-geo-localization-benchmark","title":"Game4Loc: A UAV Geo-Localization Benchmark from Game Data","date":"2024-09-25","arxiv_id":"2409.16925","repositories_listed":1,"syntology":{"n":10,"n_ran":9,"n_unverified":1,"n_pointer_only":0}},{"url":"/paper/spagbol-spatial-graph-based-orientated","title":"SpaGBOL: Spatial-Graph-Based Orientated Localisation","date":"2024-09-23","arxiv_id":"2409.15514","repositories_listed":1,"syntology":null}],"syntology_records":13,"syntology_note":"a paper without a record is not a recorded non-run: it may lack an arXiv id or simply be absent from the graph layer"},"description_links":{"kept":0,"unwrapped_to_text":0,"bare_urls_linked":0,"relative_images_dropped":0,"rule":"internal links are kept only when the target slug exists in the catalog"},"syntology":{"read_at":"2026-09-24T18:15:14+00:00","claim":"Per-sample execution status on synthesized fixtures ('ran N of M samples'); not a correctness claim and not a ranking signal.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"}},"not_shown":{"libraries":"the archive has no per-task library table","trend_sparklines":"the Trend column of the benchmarks table was a rendered image; it is not in the archive","social_and_latest_sorts":"stars and social signals are not in the archive"}}