{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,5]],"date-time":"2025-12-05T12:22:12Z","timestamp":1764937332853,"version":"3.37.3"},"reference-count":31,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"am","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000038","name":"Canada Research Chairs Fund Program and Natural Sciences and Engineering Research Council of Canada through the Discovery Grant Project","doi-asserted-by":"publisher","award":["RGPIN\/1056-2017"],"award-info":[{"award-number":["RGPIN\/1056-2017"]}],"id":[{"id":"10.13039\/501100000038","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/access.2021.3123169","type":"journal-article","created":{"date-parts":[[2021,10,26]],"date-time":"2021-10-26T20:40:02Z","timestamp":1635280802000},"page":"146244-146255","source":"Crossref","is-referenced-by-count":5,"title":["LiCaNext: Incorporating Sequential Range Residuals for Additional Advancement in Joint Perception and Motion Prediction"],"prefix":"10.1109","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6632-6068","authenticated-orcid":false,"given":"Yasser H.","family":"Khalil","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7939-7212","authenticated-orcid":false,"given":"Hussein T.","family":"Mouftah","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref31","first-page":"4679","article-title":"Deep multi-task learning for joint localization, perception, and prediction","author":"phillips","year":"2021","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01136"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1117\/1.JEI.26.2.023025"},{"key":"ref11","first-page":"1630","article-title":"Automatic signal clearance system using density based traffic control","author":"annabel","year":"2021","journal-title":"Proc 5th Int Conf Trends Electron Informat (ICOEI)"},{"key":"ref12","article-title":"RST-MODNet: Real-time spatio-temporal moving object detection for autonomous driving","author":"ramzy","year":"2019","journal-title":"arXiv 1912 00438"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2019.00293"},{"key":"ref14","first-page":"8125","article-title":"Motion U-Net: Multi-cue encoder-decoder network for motion segmentation","author":"rahmon","year":"2021","journal-title":"Proc Int Conf Pattern Recognit (ICPR)"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.04.088"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01164"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298925"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8202211"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2018.8569744"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00376"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01140"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01157"},{"key":"ref3","first-page":"1111","article-title":"Integration of motion prediction with end-to-end latent RL for self-driving vehicles","author":"khalil","year":"2021","journal-title":"Proc Int Wireless Commun Mobile Comput (IWCMC)"},{"key":"ref6","article-title":"LiRaNet: End-to-end trajectory prediction using spatio-temporal radar fusion","author":"shah","year":"2020","journal-title":"arXiv 2010 00731"},{"key":"ref29","article-title":"Spatially-aware graph neural networks for relational behavior forecasting from sensor data","author":"casas","year":"2019","journal-title":"arXiv 1910 08233"},{"key":"ref5","article-title":"Multi-view fusion of sensor data for improved perception and prediction in autonomous driving","author":"fadadu","year":"2020","journal-title":"arXiv 2008 11901"},{"key":"ref8","article-title":"Moving object segmentation in 3D LiDAR data: A learning-based approach exploiting sequential data","author":"chen","year":"2021","journal-title":"arXiv 2105 08971"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2020.3047793"},{"key":"ref2","first-page":"2.1","article-title":"End-to-end multi-view fusion for enhanced perception and motion prediction","author":"khalil","year":"2021","journal-title":"Proc 94th IEEE Veh Techol Conf"},{"key":"ref9","article-title":"Extended image differencing for change detection in UAV video mosaics","volume":"9026","author":"saur","year":"2014","journal-title":"Proc SPIE"},{"key":"ref1","article-title":"LiCaNet: Further enhancement of joint perception and motion prediction based on multi-modal fusion","author":"khalil","year":"0","journal-title":"IEEE Open J Intell Transp Syst"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2017.8206198"},{"key":"ref22","article-title":"BEV-MODNet: Monocular camera based bird’s eye view moving object detection for autonomous driving","author":"rashed","year":"2021","journal-title":"arXiv 2107 04937"},{"key":"ref21","article-title":"Monocular instance motion segmentation for autonomous driving: KITTI instancemotseg dataset and multi-task baseline","author":"mohamed","year":"2020","journal-title":"arXiv 2008 07008"},{"key":"ref24","first-page":"947","article-title":"IntentNet: Learning to predict intention from raw sensor data","author":"casas","year":"2018","journal-title":"Proc Conf Robot Learn"},{"key":"ref23","article-title":"MultiXNet: Multiclass multistage multimodal motion prediction","author":"djuric","year":"2020","journal-title":"arXiv 2006 02000"},{"key":"ref26","first-page":"2865","article-title":"MVFuseNet: Improving end-to-end object detection and motion forecasting through multi-view fusion of LiDAR data","author":"laddha","year":"2021","journal-title":"Proc IEEE Conf Comput Vis and Pattern Recog"},{"key":"ref25","article-title":"RV-FuseNet: Range view based fusion of time-series LiDAR data for joint 3D object detection and motion forecasting","author":"laddha","year":"2020","journal-title":"arXiv 2005 10863"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/9312710\/09585703.pdf?arnumber=9585703","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,7]],"date-time":"2022-02-07T21:11:37Z","timestamp":1644268297000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9585703\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":31,"URL":"https:\/\/doi.org\/10.1109\/access.2021.3123169","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2021]]}}}