{"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/end-to-end-interpretation-of-the-french","title":"End-to-End Interpretation of the French Street Name Signs Dataset","arxiv_id":"1702.03970","date":"2017-02-13","proceeding":null,"authors":["Raymond Smith","Chunhui Gu","Dar-Shyang Lee","Huiyi Hu","Ranjith Unnikrishnan","Julian Ibarz","Sacha Arnoud","Sophia Lin"],"abstract":"We introduce the French Street Name Signs (FSNS) Dataset consisting of more\nthan a million images of street name signs cropped from Google Street View\nimages of France. Each image contains several views of the same street name\nsign. Every image has normalized, title case folded ground-truth text as it\nwould appear on a map. We believe that the FSNS dataset is large and complex\nenough to train a deep network of significant complexity to solve the street\nname extraction problem \"end-to-end\" or to explore the design trade-offs\nbetween a single complex engineered network and multiple sub-networks designed\nand trained to solve sub-problems. We present such an \"end-to-end\"\nnetwork/graph for Tensor Flow and its results on the FSNS dataset.","url_abs":"http://arxiv.org/abs/1702.03970v1","url_pdf":"http://arxiv.org/pdf/1702.03970v1.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":[{"paper_slug":"end-to-end-interpretation-of-the-french","repo_url":"https://github.com/LinearPi/OCR_Chinese","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"end-to-end-interpretation-of-the-french","repo_url":"https://github.com/OzHsu23/chineseocr","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"end-to-end-interpretation-of-the-french","repo_url":"https://github.com/witcher425/CHINESEOCR","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"end-to-end-interpretation-of-the-french","repo_url":"https://github.com/xiaofengShi/CHINESE-OCR","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"optical-character-recognition","task_name":"Optical Character Recognition (OCR)"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/optical-character-recognition-on-fsns-test","task":"Optical Character Recognition (OCR)","dataset":"FSNS - Test","model":"STREET","rank_in_archive_order":3,"of":3,"metrics":{"Sequence error":"27.54"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}