{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,22]],"date-time":"2025-03-22T12:19:08Z","timestamp":1742645948894,"version":"3.28.0"},"reference-count":63,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,6,1]],"date-time":"2023-06-01T00:00:00Z","timestamp":1685577600000},"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":[],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1109\/cvpr52729.2023.00900","type":"proceedings-article","created":{"date-parts":[[2023,8,22]],"date-time":"2023-08-22T17:30:52Z","timestamp":1692725452000},"page":"9329-9339","source":"Crossref","is-referenced-by-count":6,"title":["MoDAR: Using Motion Forecasting for 3D Object Detection in Point Cloud Sequences"],"prefix":"10.1109","author":[{"given":"Yingwei","family":"Li","sequence":"first","affiliation":[{"name":"Waymo LLC"}]},{"given":"Charles R.","family":"Qi","sequence":"additional","affiliation":[{"name":"Waymo LLC"}]},{"given":"Yin","family":"Zhou","sequence":"additional","affiliation":[{"name":"Waymo LLC"}]},{"given":"Chenxi","family":"Liu","sequence":"additional","affiliation":[{"name":"Waymo LLC"}]},{"given":"Dragomir","family":"Anguelov","sequence":"additional","affiliation":[{"name":"Waymo LLC"}]}],"member":"263","reference":[{"doi-asserted-by":"publisher","key":"ref13","DOI":"10.1007\/978-3-031-19839-7_23"},{"doi-asserted-by":"publisher","key":"ref57","DOI":"10.1109\/CVPR42600.2020.00170"},{"doi-asserted-by":"publisher","key":"ref12","DOI":"10.1109\/ICCV48922.2021.01502"},{"key":"ref56","article-title":"Dcms: Motion forecasting with dual consis-tency and multi-pseudo-target supervision","author":"ye","year":"2022","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref15","DOI":"10.1109\/CVPR.2019.01298"},{"doi-asserted-by":"publisher","key":"ref59","DOI":"10.1109\/CVPR46437.2021.01161"},{"doi-asserted-by":"publisher","key":"ref14","DOI":"10.1109\/IROS.2018.8594049"},{"key":"ref58","article-title":"Multimodal virtual point 3d detection","author":"yin","year":"2021","journal-title":"Advances in neural information processing systems"},{"doi-asserted-by":"publisher","key":"ref53","DOI":"10.1109\/CVPR42600.2020.01105"},{"doi-asserted-by":"publisher","key":"ref52","DOI":"10.1109\/CVPR.2018.00798"},{"key":"ref11","article-title":"Afdet: Anchor free one stage 3d object detection","author":"ge","year":"2020","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref55","DOI":"10.1109\/CVPR46437.2021.00190"},{"doi-asserted-by":"publisher","key":"ref10","DOI":"10.1109\/CVPR52688.2022.00827"},{"year":"2018","author":"yang","journal-title":"IPOD Intensive point-based object detector for point cloud","key":"ref54"},{"doi-asserted-by":"publisher","key":"ref17","DOI":"10.1109\/IROS.2017.8205955"},{"key":"ref16","article-title":"Lidaraugment: Searching for scalable 3d lidar data augmentations","author":"leng","year":"2022","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref19","DOI":"10.1109\/CVPR52688.2022.01667"},{"doi-asserted-by":"publisher","key":"ref18","DOI":"10.15607\/RSS.2016.XII.042"},{"key":"ref51","article-title":"Auto4d: Learning to label 4d objects from sequential point clouds","author":"yang","year":"2021","journal-title":"ArXiv Preprint"},{"key":"ref50","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"},{"doi-asserted-by":"publisher","key":"ref46","DOI":"10.1007\/978-3-030-58542-6_2"},{"doi-asserted-by":"publisher","key":"ref45","DOI":"10.15607\/RSS.2015.XI.035"},{"doi-asserted-by":"publisher","key":"ref48","DOI":"10.1109\/CVPR42600.2020.01140"},{"key":"ref47","first-page":"6","article-title":"A baseline for 3d multi-object tracking","volume":"1","author":"weng","year":"2019","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref42","DOI":"10.1109\/ICRA46639.2022.9812107"},{"doi-asserted-by":"publisher","key":"ref41","DOI":"10.1109\/CVPR46437.2021.00567"},{"doi-asserted-by":"publisher","key":"ref44","DOI":"10.1109\/CVPR46437.2021.01162"},{"doi-asserted-by":"publisher","key":"ref43","DOI":"10.1109\/CVPR42600.2020.00466"},{"doi-asserted-by":"publisher","key":"ref49","DOI":"10.1109\/CVPR52688.2022.00534"},{"doi-asserted-by":"publisher","key":"ref8","DOI":"10.1109\/ICRA.2017.7989161"},{"key":"ref7","article-title":"Mppnet: Multi-frame feature intertwining with proxy points for 3d temporal object detection","author":"chen","year":"0","journal-title":"European Conference on Computer Vision"},{"doi-asserted-by":"publisher","key":"ref9","DOI":"10.1109\/ICCV48922.2021.00957"},{"key":"ref4","first-page":"947","article-title":"Intentnet: Learning to predict intention from raw sensor data","author":"casas","year":"0","journal-title":"Conference on Robot Learning"},{"key":"ref3","first-page":"11621","article-title":"nuscenes: A multi-modal dataset for autonomous driving","author":"caesar","year":"0","journal-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"},{"doi-asserted-by":"publisher","key":"ref6","DOI":"10.1109\/3468.798073"},{"doi-asserted-by":"publisher","key":"ref5","DOI":"10.1109\/CVPR46437.2021.01417"},{"key":"ref40","article-title":"Swformer: Sparse window transformer for 3d object detection in point clouds","author":"sun","year":"0","journal-title":"European Conference on Computer Vision"},{"doi-asserted-by":"publisher","key":"ref35","DOI":"10.1109\/CVPR42600.2020.00178"},{"key":"ref34","article-title":"Pointr-cnn: 3d object proposal generation and detection from point cloud","author":"shi","year":"2018","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref37","DOI":"10.1016\/j.imavis.2021.104117"},{"key":"ref36","first-page":"0","article-title":"Complex-yolo: An euler-region-proposal for real-time 3d object detection on point clouds","author":"simony","year":"0","journal-title":"Proceedings of the European Conference on Computer Vision (ECCV) Workshops"},{"doi-asserted-by":"publisher","key":"ref31","DOI":"10.1109\/ICCV.2019.00937"},{"doi-asserted-by":"publisher","key":"ref30","DOI":"10.1080\/014311698215748"},{"doi-asserted-by":"publisher","key":"ref33","DOI":"10.1109\/CVPR46437.2021.00607"},{"doi-asserted-by":"publisher","key":"ref32","DOI":"10.1109\/CVPR.2018.00102"},{"key":"ref2","article-title":"Range conditioned dilated convolutions for scale invariant 3d object detection","author":"bewley","year":"2020","journal-title":"ArXiv Preprint"},{"key":"ref1","article-title":"Chauf-feurnet: Learning to drive by imitating the best and synthesizing the worst","author":"bansal","year":"2018","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref39","DOI":"10.1109\/CVPR42600.2020.00252"},{"doi-asserted-by":"publisher","key":"ref38","DOI":"10.1109\/CVPR.2016.94"},{"doi-asserted-by":"publisher","key":"ref24","DOI":"10.1109\/CVPR.2019.01296"},{"doi-asserted-by":"publisher","key":"ref23","DOI":"10.1109\/CVPR.2018.00376"},{"key":"ref26","article-title":"Starnet: Targeted computation for object detection in point clouds","author":"ngiam","year":"2019","journal-title":"CoRR"},{"key":"ref25","article-title":"Wayformer: Motion forecasting via simple & efficient attention networks","author":"nayakanti","year":"2022","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref20","DOI":"10.1109\/CVPR42600.2020.01157"},{"doi-asserted-by":"publisher","key":"ref63","DOI":"10.1109\/CVPR.2018.00472"},{"doi-asserted-by":"publisher","key":"ref22","DOI":"10.1109\/CVPR46437.2021.00749"},{"doi-asserted-by":"publisher","key":"ref21","DOI":"10.1007\/978-3-031-19803-8_10"},{"doi-asserted-by":"publisher","key":"ref28","DOI":"10.1109\/CVPR52688.2022.01669"},{"key":"ref27","article-title":"Scene transformer: A unified architecture for predicting multiple agent trajectories","author":"ngiam","year":"2021","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref29","DOI":"10.1109\/ICCV48922.2021.01515"},{"doi-asserted-by":"publisher","key":"ref60","DOI":"10.1109\/IROS51168.2021.9636035"},{"key":"ref62","article-title":"Objects as points","author":"zhou","year":"2019","journal-title":"ArXiv Preprint"},{"doi-asserted-by":"publisher","key":"ref61","DOI":"10.1109\/CVPR42600.2020.01136"}],"event":{"name":"2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","start":{"date-parts":[[2023,6,17]]},"location":"Vancouver, BC, Canada","end":{"date-parts":[[2023,6,24]]}},"container-title":["2023 IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10203037\/10203050\/10205140.pdf?arnumber=10205140","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,11]],"date-time":"2023-09-11T17:54:43Z","timestamp":1694454883000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10205140\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6]]},"references-count":63,"URL":"https:\/\/doi.org\/10.1109\/cvpr52729.2023.00900","relation":{},"subject":[],"published":{"date-parts":[[2023,6]]}}}