{"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/exploring-models-and-data-for-remote-sensing","title":"Exploring Models and Data for Remote Sensing Image Caption Generation","arxiv_id":"1712.07835","date":"2017-12-21","proceeding":null,"authors":["Xiaoqiang Lu","Binqiang Wang","Xiangtao Zheng","Xuelong. Li"],"abstract":"Inspired by recent development of artificial satellite, remote sensing images\nhave attracted extensive attention. Recently, noticeable progress has been made\nin scene classification and target detection.However, it is still not clear how\nto describe the remote sensing image content with accurate and concise\nsentences. In this paper, we investigate to describe the remote sensing images\nwith accurate and flexible sentences. First, some annotated instructions are\npresented to better describe the remote sensing images considering the special\ncharacteristics of remote sensing images. Second, in order to exhaustively\nexploit the contents of remote sensing images, a large-scale aerial image data\nset is constructed for remote sensing image caption. Finally, a comprehensive\nreview is presented on the proposed data set to fully advance the task of\nremote sensing caption. Extensive experiments on the proposed data set\ndemonstrate that the content of the remote sensing image can be completely\ndescribed by generating language descriptions. The data set is available at\nhttps://github.com/201528014227051/RSICD_optimal","url_abs":"http://arxiv.org/abs/1712.07835v1","url_pdf":"http://arxiv.org/pdf/1712.07835v1.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":"exploring-models-and-data-for-remote-sensing","repo_url":"https://github.com/201528014227051/RSICD_optimal","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"exploring-models-and-data-for-remote-sensing","repo_url":"https://github.com/arampacha/clip-rsicd","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"jax","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"caption-generation","task_name":"Caption Generation"},{"task_slug":"image-to-text-retrieval","task_name":"Image-to-Text Retrieval"},{"task_slug":"scene-classification","task_name":"Scene Classification"}],"methods":[],"datasets_introduced":[{"slug":"rsicd","name":"RSICD","full_name":"Remote Sensing Image Captioning Dataset"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1712.07835","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}