{"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/ipod-intensive-point-based-object-detector","title":"IPOD: Intensive Point-based Object Detector for Point Cloud","arxiv_id":"1812.05276","date":"2018-12-13","proceeding":null,"authors":["Zetong Yang","Yanan sun","Shu Liu","Xiaoyong Shen","Jiaya Jia"],"abstract":"We present a novel 3D object detection framework, named IPOD, based on raw\npoint cloud. It seeds object proposal for each point, which is the basic\nelement. This paradigm provides us with high recall and high fidelity of\ninformation, leading to a suitable way to process point cloud data. We design\nan end-to-end trainable architecture, where features of all points within a\nproposal are extracted from the backbone network and achieve a proposal feature\nfor final bounding inference. These features with both context information and\nprecise point cloud coordinates yield improved performance. We conduct\nexperiments on KITTI dataset, evaluating our performance in terms of 3D object\ndetection, Bird's Eye View (BEV) detection and 2D object detection. Our method\naccomplishes new state-of-the-art , showing great advantage on the hard set.","url_abs":"http://arxiv.org/abs/1812.05276v1","url_pdf":"http://arxiv.org/pdf/1812.05276v1.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":"2d-object-detection","task_name":"2D Object Detection"},{"task_slug":"3d-object-detection","task_name":"3D Object Detection"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-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":"IPOD","rank_in_archive_order":23,"of":26,"metrics":{"AP":"79.75%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-cars-hard","task":"3D Object Detection","dataset":"KITTI Cars Hard","model":"IPOD","rank_in_archive_order":20,"of":25,"metrics":{"AP":"66.33%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-cyclists-easy","task":"3D Object Detection","dataset":"KITTI Cyclists Easy","model":"IPOD","rank_in_archive_order":10,"of":12,"metrics":{"AP":"71.40%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-cyclists-hard","task":"3D Object Detection","dataset":"KITTI Cyclists Hard","model":"IPOD","rank_in_archive_order":10,"of":12,"metrics":{"AP":"48.34%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-cyclists","task":"3D Object Detection","dataset":"KITTI Cyclists Moderate","model":"IPOD","rank_in_archive_order":11,"of":13,"metrics":{"AP":"53.46%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-pedestrians-easy","task":"3D Object Detection","dataset":"KITTI Pedestrians Easy","model":"IPOD","rank_in_archive_order":1,"of":9,"metrics":{"AP":"56.92%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-pedestrians-hard","task":"3D Object Detection","dataset":"KITTI Pedestrians Hard","model":"IPOD","rank_in_archive_order":2,"of":9,"metrics":{"AP":"42.39%"},"uses_additional_data":false},{"leaderboard":"/sota/3d-object-detection-on-kitti-pedestrians","task":"3D Object Detection","dataset":"KITTI Pedestrians Moderate","model":"IPOD","rank_in_archive_order":4,"of":12,"metrics":{"AP":"44.68%"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1812.05276","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}