{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T23:34:28Z","timestamp":1781739268201,"version":"3.54.5"},"reference-count":32,"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:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100020275","name":"Vilnius University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100020275","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3331678","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T19:07:01Z","timestamp":1699470421000},"page":"128421-128428","source":"Crossref","is-referenced-by-count":2,"title":["Visual Place Recognition Pre-Training for End-to-End Trained Autonomous Driving Agent"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7906-5688","authenticated-orcid":false,"given":"Shubham","family":"Juneja","sequence":"first","affiliation":[{"name":"Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5977-827X","authenticated-orcid":false,"given":"Povilas","family":"Daniu\u0161is","sequence":"additional","affiliation":[{"name":"Neurotechnology, Vilnius, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2281-4035","authenticated-orcid":false,"given":"Virginijus","family":"Marcinkevi\u010dius","sequence":"additional","affiliation":[{"name":"Institute of Data Science and Digital Technologies, Vilnius University, Vilnius, Lithuania"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.01494"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00391"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-06430-2_38"},{"key":"ref14","first-page":"20703","article-title":"Model-based imitation learning for urban driving","volume":"35","author":"hu","year":"2022","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref31","first-page":"1","article-title":"PyTorch: An imperative style, high-performance deep learning library","volume":"32","author":"paszke","year":"2019","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref30","first-page":"1","article-title":"CARLA: An open urban driving simulator","author":"dosovitskiy","year":"2017","journal-title":"Proc Conf Robot Learn"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/s10514-021-09980-x"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2020.3043505"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MITS.2014.2306552"},{"key":"ref17","first-page":"1","article-title":"End to end learning for self-driving cars","volume":"abs 1604 7316","author":"bojarski","year":"2016","journal-title":"CoRR"},{"key":"ref16","first-page":"305","article-title":"ALVINN: An autonomous land vehicle in a neural network","author":"pomerleau","year":"1988","journal-title":"Proc 1st Int Conf Neural Inf Process Syst (NIPS)"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00942"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/ICRA.2018.8460487"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.351"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01712"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1007\/978-3-319-10602-1_48","article-title":"Microsoft COCO: Common objects in context","author":"lin","year":"2014","journal-title":"Computer Vision—ECCV 2014"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.322"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19839-7_31"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"12878","DOI":"10.1109\/TPAMI.2022.3200245","article-title":"TransFuser: Imitation with transformer-based sensor fusion for autonomous driving","volume":"45","author":"chitta","year":"2023","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"ref21","first-page":"6119","article-title":"Trajectory-guided control prediction for end-to-end autonomous driving: A simple yet strong baseline","author":"wu","year":"2022","journal-title":"Proc NeurIPS"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-19809-0_7"},{"key":"ref27","first-page":"24639","article-title":"Video pretraining (VPT): Learning to act by watching unlabeled online videos","volume":"35","author":"baker","year":"2022","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","first-page":"1","article-title":"Policy pre-training for autonomous driving via self-supervised geometric modeling","author":"wu","year":"2023","journal-title":"Proc Int Conf Learn Represent"},{"key":"ref8","first-page":"1877","article-title":"Language models are few-shot learners","volume":"33","author":"brown","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01178"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00277"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1561\/2300000053"},{"key":"ref3","article-title":"End-to-end autonomous driving: Challenges and frontiers","author":"chen","year":"2023","journal-title":"arXiv 2306 16927"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10857"},{"key":"ref5","first-page":"627","article-title":"A reduction of imitation learning and structured prediction to no-regret online learning","volume":"15","author":"ross","year":"2010","journal-title":"J Mach Learn Res"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/10005208\/10313277.pdf?arnumber=10313277","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T18:03:18Z","timestamp":1730484198000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10313277\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":32,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3331678","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]}}}