{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T07:04:08Z","timestamp":1773903848891,"version":"3.50.1"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Instrum. Meas."],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/tim.2023.3301907","type":"journal-article","created":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T17:59:02Z","timestamp":1691431142000},"page":"1-12","source":"Crossref","is-referenced-by-count":8,"title":["Voxel Graph Attention for 3-D Object Detection From Point Clouds"],"prefix":"10.1109","volume":"72","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8650-444X","authenticated-orcid":false,"given":"Bin","family":"Lu","sequence":"first","affiliation":[{"name":"Control and Compute Engineering, North China Electric Power University, Baoding, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7062-931X","authenticated-orcid":false,"given":"Yang","family":"Sun","sequence":"additional","affiliation":[{"name":"Control and Compute Engineering, North China Electric Power University, Baoding, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0833-2467","authenticated-orcid":false,"given":"Zhenyu","family":"Yang","sequence":"additional","affiliation":[{"name":"Control and Compute Engineering, North China Electric Power University, Baoding, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00086"},{"key":"ref35","first-page":"2647","article-title":"From points to parts: 3D object detection from point cloud with part-aware and part-aggregation network","volume":"43","author":"shi","year":"2021","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00939"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00204"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00738"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00170"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01105"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i07.6837"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33019267"},{"key":"ref30","first-page":"641","article-title":"Deep continuous fusion for multi-sensor 3D object detection","author":"liang","year":"2018","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00178"},{"key":"ref33","first-page":"720","article-title":"3D-CVF: Generating joint camera and LiDAR features using cross-view spatial feature fusion for 3D object detection","author":"yoo","year":"2020","journal-title":"Proc Eur Conf Comput Vis"},{"key":"ref10","first-page":"8459","article-title":"Point density-aware voxels for LiDAR 3D object detection","author":"hu","year":"2022","journal-title":"Proc IEEE\/CVF Conf Comput Vis Pattern Recognit (CVPR)"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00752"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-018-1070-x"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1080\/10589759.2022.2074415"},{"key":"ref17","article-title":"3D object detection for autonomous driving: A comprehensive survey","author":"mao","year":"2022","journal-title":"arXiv 2206 09474"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00746"},{"key":"ref16","article-title":"Attention is all you need","volume":"30","author":"vaswani","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01189"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"3337","DOI":"10.3390\/s18103337","article-title":"SECOND: Sparsely embedded convolutional detection","volume":"18","author":"yan","year":"2018","journal-title":"SENSORS"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00472"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.324"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00823"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.2978386"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2022.3201469"},{"key":"ref26","article-title":"A disciplined approach to neural network hyper-parameters: Part 1—Learning rate, batch size, momentum, and weight decay","author":"smith","year":"2018","journal-title":"arXiv 1803 09820"},{"key":"ref25","article-title":"3D object proposals for accurate object class detection","volume":"28","author":"chen","year":"2015","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00315"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01298"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2022.108524"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01426"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.3390\/s20030704"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-20077-9_32"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i4.16470"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00098"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8594049"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.691"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00102"},{"key":"ref8","article-title":"PointNet++: Deep hierarchical feature learning on point sets in a metric space","volume":"30","author":"qi","year":"2017","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.16"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00274"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2022.3203163"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3019187"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01054"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i2.16207"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2020.3031371"}],"container-title":["IEEE Transactions on Instrumentation and Measurement"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/19\/10012124\/10210325.pdf?arnumber=10210325","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T18:01:04Z","timestamp":1694455264000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10210325\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/tim.2023.3301907","relation":{},"ISSN":["0018-9456","1557-9662"],"issn-type":[{"value":"0018-9456","type":"print"},{"value":"1557-9662","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}