{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/location-recognition-over-large-time-lags","title":"Location Recognition Over Large Time Lags","arxiv_id":"1409.7556","date":"2014-09-26","proceeding":null,"authors":["Basura Fernando","Tatiana Tommasi","Tinne Tuytelaars"],"abstract":"Would it be possible to automatically associate ancient pictures to modern\nones and create fancy cultural heritage city maps? We introduce here the task\nof recognizing the location depicted in an old photo given modern annotated\nimages collected from the Internet. We present an extensive analysis on\ndifferent features, looking for the most discriminative and most robust to the\nimage variability induced by large time lags. Moreover, we show that the\ndescribed task benefits from domain adaptation.","url_abs":"http://arxiv.org/abs/1409.7556v3","url_pdf":"http://arxiv.org/pdf/1409.7556v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"}],"methods":[],"datasets_introduced":[{"slug":"large-time-lags-location-ltll","name":"Large Time Lags Location (LTLL)","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}