{"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/a-general-pipeline-for-3d-detection-of","title":"A General Pipeline for 3D Detection of Vehicles","arxiv_id":"1803.00387","date":"2018-02-12","proceeding":null,"authors":["Xinxin Du","Marcelo H. Ang Jr.","Sertac Karaman","Daniela Rus"],"abstract":"Autonomous driving requires 3D perception of vehicles and other objects in\nthe in environment. Much of the current methods support 2D vehicle detection.\nThis paper proposes a flexible pipeline to adopt any 2D detection network and\nfuse it with a 3D point cloud to generate 3D information with minimum changes\nof the 2D detection networks. To identify the 3D box, an effective model\nfitting algorithm is developed based on generalised car models and score maps.\nA two-stage convolutional neural network (CNN) is proposed to refine the\ndetected 3D box. This pipeline is tested on the KITTI dataset using two\ndifferent 2D detection networks. The 3D detection results based on these two\nnetworks are similar, demonstrating the flexibility of the proposed pipeline.\nThe results rank second among the 3D detection algorithms, indicating its\ncompetencies in 3D detection.","url_abs":"http://arxiv.org/abs/1803.00387v1","url_pdf":"http://arxiv.org/pdf/1803.00387v1.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":"3d-object-detection","task_name":"3D Object Detection"},{"task_slug":"autonomous-driving","task_name":"Autonomous Driving"},{"task_slug":"vehicle-detection","task_name":"vehicle detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/3d-object-detection-on-kitti-cars-easy","task":"3D Object Detection","dataset":"KITTI Cars Easy","model":"PC-CNN-V2","rank_in_archive_order":18,"of":26,"metrics":{"AP":"84.33%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-cars-hard","task":"3D Object Detection","dataset":"KITTI Cars Hard","model":"PC-CNN-V2","rank_in_archive_order":21,"of":25,"metrics":{"AP":"64.83%"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1803.00387","atlas_url":"https://app.syntology.ai/?focus=1803.00387","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}