{"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/learning-to-map-vehicles-into-birds-eye-view","title":"Learning to Map Vehicles into Bird's Eye View","arxiv_id":"1706.08442","date":"2017-06-26","proceeding":null,"authors":["Andrea Palazzi","Guido Borghi","Davide Abati","Simone Calderara","Rita Cucchiara"],"abstract":"Awareness of the road scene is an essential component for both autonomous\nvehicles and Advances Driver Assistance Systems and is gaining importance both\nfor the academia and car companies. This paper presents a way to learn a\nsemantic-aware transformation which maps detections from a dashboard camera\nview onto a broader bird's eye occupancy map of the scene. To this end, a huge\nsynthetic dataset featuring 1M couples of frames, taken from both car dashboard\nand bird's eye view, has been collected and automatically annotated. A\ndeep-network is then trained to warp detections from the first to the second\nview. We demonstrate the effectiveness of our model against several baselines\nand observe that is able to generalize on real-world data despite having been\ntrained solely on synthetic ones.","url_abs":"http://arxiv.org/abs/1706.08442v1","url_pdf":"http://arxiv.org/pdf/1706.08442v1.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":"learning-to-map-vehicles-into-birds-eye-view","repo_url":"https://github.com/Ceachi/Project-Self-Driving-Car-Advanced-Lane-Lines","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"learning-to-map-vehicles-into-birds-eye-view","repo_url":"https://github.com/cciprianmihai/Self_Driving_Car_NanoDegree_P2_AdvancedLaneLines","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"learning-to-map-vehicles-into-birds-eye-view","repo_url":"https://github.com/mirkozaff/DeepGTAPrediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"autonomous-vehicles","task_name":"Autonomous Vehicles"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}