{"id":"https://openalex.org/W4401327080","doi":"https://doi.org/10.1109/tits.2024.3433591","title":"BEV-TP: End-to-End Visual Perception and Trajectory Prediction for Autonomous Driving","display_name":"BEV-TP: End-to-End Visual Perception and Trajectory Prediction for Autonomous Driving","publication_year":2024,"publication_date":"2024-08-05","ids":{"openalex":"https://openalex.org/W4401327080","doi":"https://doi.org/10.1109/tits.2024.3433591"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3433591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3433591","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086522441","display_name":"Bo Lang","orcid":"https://orcid.org/0000-0002-0586-3783"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Lang","raw_affiliation_strings":["Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0586-3783","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100627986","display_name":"Xin Li","orcid":"https://orcid.org/0000-0002-1007-1000"},"institutions":[{"id":"https://openalex.org/I4210087596","display_name":"Qualcomm (United States)","ror":"https://ror.org/002zrf773","country_code":"US","type":"company","lineage":["https://openalex.org/I4210087596"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Qualcomm AI Research, Qualcomm Technologies, Inc., San Diego, CA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1007-1000","affiliations":[{"raw_affiliation_string":"Qualcomm AI Research, Qualcomm Technologies, Inc., San Diego, CA, USA","institution_ids":["https://openalex.org/I4210087596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046998111","display_name":"Mooi Choo Chuah","orcid":"https://orcid.org/0000-0002-0117-0621"},"institutions":[{"id":"https://openalex.org/I186143895","display_name":"Lehigh University","ror":"https://ror.org/012afjb06","country_code":"US","type":"education","lineage":["https://openalex.org/I186143895"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mooi Choo Chuah","raw_affiliation_strings":["Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA"],"raw_orcid":"https://orcid.org/0000-0002-0117-0621","affiliations":[{"raw_affiliation_string":"Computer Science and Engineering, Lehigh University, Bethlehem, PA, USA","institution_ids":["https://openalex.org/I186143895"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.6525,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82434783,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"25","issue":"11","first_page":"18537","last_page":"18546"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9498000144958496,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.7326648235321045},{"id":"https://openalex.org/keywords/end-to-end-principle","display_name":"End-to-end principle","score":0.7043710350990295},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.6224743127822876},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5122832655906677},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4040159285068512},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36079758405685425},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.36012089252471924},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.3302174210548401},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.13119396567344666},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.10065048933029175}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7326648235321045},{"id":"https://openalex.org/C74296488","wikidata":"https://www.wikidata.org/wiki/Q2527392","display_name":"End-to-end principle","level":2,"score":0.7043710350990295},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.6224743127822876},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5122832655906677},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4040159285068512},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36079758405685425},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.36012089252471924},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.3302174210548401},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.13119396567344666},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.10065048933029175},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3433591","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3433591","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5598698715","display_name":null,"funder_award_id":"CPS 1931867","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W2606355385","https://openalex.org/W2897529137","https://openalex.org/W2908510526","https://openalex.org/W2951021014","https://openalex.org/W2963727135","https://openalex.org/W2963759562","https://openalex.org/W2968296999","https://openalex.org/W2969987486","https://openalex.org/W3012573144","https://openalex.org/W3026544131","https://openalex.org/W3034295100","https://openalex.org/W3034782805","https://openalex.org/W3035054225","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3095753995","https://openalex.org/W3096609285","https://openalex.org/W3109395584","https://openalex.org/W3114753236","https://openalex.org/W3116651890","https://openalex.org/W3119686997","https://openalex.org/W3127587661","https://openalex.org/W3132607695","https://openalex.org/W3138516171","https://openalex.org/W3139491754","https://openalex.org/W3167095230","https://openalex.org/W3167949052","https://openalex.org/W3177645420","https://openalex.org/W3204875639","https://openalex.org/W3214282487","https://openalex.org/W4210457203","https://openalex.org/W4214530037","https://openalex.org/W4225422725","https://openalex.org/W4225793049","https://openalex.org/W4226305814","https://openalex.org/W4289752563","https://openalex.org/W4297785339","https://openalex.org/W4310828996","https://openalex.org/W4312473433","https://openalex.org/W4312501532","https://openalex.org/W4312894406","https://openalex.org/W4385221361","https://openalex.org/W4386076439","https://openalex.org/W4390872423","https://openalex.org/W4390872833","https://openalex.org/W6679214204","https://openalex.org/W6755864109","https://openalex.org/W6757521438","https://openalex.org/W6757817989","https://openalex.org/W6760424586","https://openalex.org/W6767379092","https://openalex.org/W6777902602","https://openalex.org/W6781269497","https://openalex.org/W6782468546","https://openalex.org/W6790487882","https://openalex.org/W6793856509","https://openalex.org/W6797951480","https://openalex.org/W6802311648","https://openalex.org/W6802437797","https://openalex.org/W6804183503","https://openalex.org/W6811230113","https://openalex.org/W6840806833","https://openalex.org/W6847288970"],"related_works":["https://openalex.org/W3179968364","https://openalex.org/W1999612375","https://openalex.org/W1941703695","https://openalex.org/W4248382324","https://openalex.org/W3131574667","https://openalex.org/W4323768008","https://openalex.org/W2938107654","https://openalex.org/W2151749779","https://openalex.org/W3008587939","https://openalex.org/W2087303720"],"abstract_inverted_index":{"For":[0],"autonomous":[1],"vehicles":[2],"(AVs),":[3],"the":[4,23,45,54,63,66,125,137,177,181],"ability":[5],"for":[6,85,140],"effective":[7],"end-to-end":[8],"perception":[9,27,46,49,88],"and":[10,28,89,100,121,131,156,167],"future":[11,157],"trajectory":[12,90,170],"prediction":[13,29,35,55,67,171],"is":[14],"critical":[15],"in":[16],"planning":[17],"a":[18,39,59,74,79,164],"safe":[19],"automatic":[20],"maneuver.":[21],"In":[22,69],"current":[24],"AVs":[25],"systems,":[26],"are":[30,114,148],"two":[31],"separate":[32],"modules.":[33],"The":[34],"module":[36,139],"receives":[37],"only":[38],"restricted":[40],"amount":[41],"of":[42,65,136,183],"information":[43,95,102],"from":[44,96,103],"module.":[47],"Furthermore,":[48],"errors":[50],"will":[51],"propagate":[52],"into":[53],"module,":[56],"ultimately":[57],"having":[58],"negative":[60],"impact":[61],"on":[62,176],"accuracy":[64],"results.":[68],"this":[70],"paper,":[71],"we":[72],"present":[73],"novel":[75],"framework":[76],"termed":[77],"BEV-TP,":[78],"visual":[80,94,119],"context-guided":[81],"center-based":[82,161],"transformer":[83,138],"network":[84],"joint":[86],"3D":[87,152],"prediction.":[91,159],"BEV-TP":[92,184],"exploits":[93],"consecutive":[97],"multi-view":[98],"images":[99],"context":[101,122],"HD":[104],"semantic":[105],"maps,":[106],"to":[107,117,150],"predict":[108],"better":[109],"objects\u2019":[110],"centers":[111],"whose":[112],"locations":[113],"then":[115],"used":[116,149],"query":[118],"features":[120,123],"via":[124],"attention":[126],"mechanism.":[127],"Generated":[128],"agent":[129],"queries":[130,133],"map":[132],"facilitate":[134],"learning":[135],"further":[141],"feature":[142],"aggregation.":[143],"Finally,":[144],"multiple":[145],"regression":[146],"heads":[147],"perform":[151],"bounding":[153],"box":[154],"detection":[155],"velocity":[158],"This":[160],"approach":[162],"achieves":[163],"differentiable,":[165],"simple,":[166],"efficient":[168],"E2E":[169],"framework.":[172],"Extensive":[173],"experiments":[174],"conducted":[175],"nuScenes":[178],"dataset":[179],"demonstrate":[180],"effectiveness":[182],"over":[185],"traditional":[186],"pipelines":[187],"with":[188],"sequential":[189],"paradigms.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":9}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}