{"id":"https://openalex.org/W4414432572","doi":"https://doi.org/10.1109/tpami.2025.3610517","title":"End-to-End Autonomous Driving Without Costly Modularization and 3D Manual Annotation","display_name":"End-to-End Autonomous Driving Without Costly Modularization and 3D Manual Annotation","publication_year":2025,"publication_date":"2025-09-23","ids":{"openalex":"https://openalex.org/W4414432572","doi":"https://doi.org/10.1109/tpami.2025.3610517","pmid":"https://pubmed.ncbi.nlm.nih.gov/40986575"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2025.3610517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3610517","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5115444828","display_name":"Mingzhe Guo","orcid":"https://orcid.org/0000-0001-6399-9753"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingzhe Guo","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhipeng Zhang","orcid":"https://orcid.org/0000-0003-0479-332X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhipeng Zhang","raw_affiliation_strings":["School of Artificial Intelligence (SAI), Shanghai Jiao Tong University (SJTU), Shanghai, China","School of Artificial Intelligence, Shanghai Jiao Tong University (SAI, SJTU), China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence (SAI), Shanghai Jiao Tong University (SJTU), Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"School of Artificial Intelligence, Shanghai Jiao Tong University (SAI, SJTU), China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061935529","display_name":"He Yuan","orcid":"https://orcid.org/0000-0001-7673-4682"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yuan He","raw_affiliation_strings":["KargoBot, Beijing, China"],"affiliations":[{"raw_affiliation_string":"KargoBot, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693413","display_name":"Ke Wang","orcid":"https://orcid.org/0000-0002-5615-0847"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke Wang","raw_affiliation_strings":["KargoBot, Beijing, China"],"affiliations":[{"raw_affiliation_string":"KargoBot, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069749738","display_name":"Liping Jing","orcid":"https://orcid.org/0000-0001-7578-3407"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liping Jing","raw_affiliation_strings":["Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, China"],"affiliations":[{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]},{"raw_affiliation_string":"Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061469520","display_name":"Haibin Ling","orcid":"https://orcid.org/0000-0003-4094-8413"},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haibin Ling","raw_affiliation_strings":["Department of Computer Science, Stony Brook University, Stony Brook, NY, USA","Department of Computer Science, Stony Brook University, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Stony Brook University, Stony Brook, NY, USA","institution_ids":["https://openalex.org/I59553526"]},{"raw_affiliation_string":"Department of Computer Science, Stony Brook University, USA","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5115444828"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":3.8237,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93637276,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"48","issue":"1","first_page":"675","last_page":"692"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9053999781608582,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9053999781608582,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/modular-design","display_name":"Modular design","score":0.6122000217437744},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5817000269889832},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5666999816894531},{"id":"https://openalex.org/keywords/pretext","display_name":"Pretext","score":0.47440001368522644},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.37940001487731934},{"id":"https://openalex.org/keywords/task-analysis","display_name":"Task analysis","score":0.36910000443458557},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.3659000098705292},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.3619000017642975}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8187999725341797},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.614799976348877},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.6122000217437744},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5817000269889832},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5666999816894531},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5302000045776367},{"id":"https://openalex.org/C2779627259","wikidata":"https://www.wikidata.org/wiki/Q779763","display_name":"Pretext","level":3,"score":0.47440001368522644},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.37940001487731934},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.36910000443458557},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.3659000098705292},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3564999997615814},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.3499999940395355},{"id":"https://openalex.org/C88482812","wikidata":"https://www.wikidata.org/wiki/Q6453666","display_name":"Modular programming","level":2,"score":0.34450000524520874},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.30160000920295715},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.2815000116825104},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2687000036239624},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.2574999928474426},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2025.3610517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2025.3610517","pdf_url":null,"source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:40986575","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/40986575","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on pattern analysis and machine intelligence","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4118857521","display_name":null,"funder_award_id":"62176020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8377820436","display_name":null,"funder_award_id":"2019JBZ110","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8689330525","display_name":null,"funder_award_id":"L211016","funder_id":"https://openalex.org/F4320322919","funder_display_name":"Natural Science Foundation of Beijing Municipality"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322919","display_name":"Natural Science Foundation of Beijing Municipality","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2922329393","https://openalex.org/W2963926543","https://openalex.org/W2968008415","https://openalex.org/W2994631335","https://openalex.org/W3009593063","https://openalex.org/W3023371261","https://openalex.org/W3035054225","https://openalex.org/W3035574168","https://openalex.org/W3041049917","https://openalex.org/W3109791956","https://openalex.org/W3116959466","https://openalex.org/W3169575318","https://openalex.org/W3172477795","https://openalex.org/W3172863135","https://openalex.org/W3174177541","https://openalex.org/W3198460218","https://openalex.org/W4206182795","https://openalex.org/W4240035482","https://openalex.org/W4248606406","https://openalex.org/W4284712624","https://openalex.org/W4312396550","https://openalex.org/W4312580801","https://openalex.org/W4312894406","https://openalex.org/W4361802179","https://openalex.org/W4382466543","https://openalex.org/W4385245566","https://openalex.org/W4386076400","https://openalex.org/W4390871914","https://openalex.org/W4390872423","https://openalex.org/W4390873009","https://openalex.org/W4390874087","https://openalex.org/W4390874575","https://openalex.org/W4402727317","https://openalex.org/W4402727673","https://openalex.org/W4402778069","https://openalex.org/W4404563280","https://openalex.org/W4404612908","https://openalex.org/W4405907309","https://openalex.org/W4413145914","https://openalex.org/W4413147287","https://openalex.org/W4413947039","https://openalex.org/W4415799242"],"related_works":[],"abstract_inverted_index":{"We":[0],"propose":[1,112],"UAD,":[2,113],"an":[3,114,118],"end-to-end":[4,38],"framework":[5,116],"with":[6,52,117],"Unsupervised":[7],"pretext":[8,140],"task":[9],"for":[10,64,251],"vision-based":[11],"Autonomous":[12],"Driving,":[13],"achieving":[14,68],"the":[15,34,45,92,136,142,147,164,167,178,193,203,219,224,242,252],"best":[16],"open-loop":[17,199],"evaluation":[18,200,211],"performance":[19,257],"in":[20,28,48,103,181,209,238,267],"nuScenes,":[21],"meanwhile":[22],"showing":[23],"robust":[24],"closed-loop":[25,210],"driving":[26,40,50,143],"quality":[27],"CARLA.":[29],"Our":[30,184,246],"motivation":[31],"stems":[32],"from":[33],"observation":[35],"that":[36],"current":[37],"autonomous":[39],"(E2EAD)":[41],"models":[42],"still":[43],"mimic":[44],"modular":[46],"architecture":[47],"typical":[49],"stacks,":[51],"carefully":[53],"designed":[54],"supervised":[55,260],"perception":[56],"and":[57,95,106,151,201,234,270],"prediction":[58],"subtasks":[59,78],"to":[60,90,121,134,176],"provide":[61],"environment":[62],"information":[63],"oriented":[65],"planning.":[66],"Although":[67],"groundbreaking":[69],"progress,":[70],"such":[71],"design":[72,128,248],"has":[73],"certain":[74],"drawbacks:":[75],"1)":[76],"preceding":[77],"require":[79],"massive":[80],"high-quality":[81],"3D":[82],"annotations":[83],"as":[84],"supervision,":[85],"posing":[86],"a":[87,129,158],"significant":[88],"impediment":[89],"scaling":[91],"training":[93,105,160,230],"data;":[94],"2)":[96],"each":[97],"submodule":[98],"entails":[99],"substantial":[100],"computation":[101],"overhead":[102],"both":[104],"inference.":[107,271],"To":[108],"this":[109],"end,":[110],"we":[111,127],"E2EAD":[115],"unsupervised<sup>1</sup>":[119],"proxy":[120],"address":[122],"all":[123],"these":[124],"issues.":[125],"Firstly,":[126],"novel":[130],"Angular":[131],"Perception":[132],"Pretext":[133],"eliminate":[135],"annotation":[137],"requirement.":[138],"The":[139],"perceives":[141],"scene":[144],"by":[145],"predicting":[146],"angular-wise":[148],"spatial":[149],"objectness":[150],"temporal":[152],"dynamics,":[153],"without":[154],"manual":[155],"annotation.":[156],"Secondly,":[157],"self-supervised":[159],"strategy,":[161],"which":[162,217],"learns":[163],"consistency":[165],"of":[166,197,207,212,232],"predicted":[168],"trajectories":[169],"under":[170],"different":[171],"augment":[172],"views,":[173],"is":[174],"proposed":[175,225],"enhance":[177],"planning":[179],"robustness":[180],"steering":[182],"scenarios.":[183],"UAD":[185],"achieves":[186],"38.7%":[187],"relative":[188],"improvements":[189],"over":[190,259],"UniAD":[191,233],"on":[192],"average":[194],"collision":[195],"rate":[196],"nuScenes":[198],"obtains":[202],"route":[204],"completion":[205],"score":[206],"98.5%":[208],"CARLA's":[213],"Town05":[214],"Long":[215],"benchmark,":[216],"outperforms":[218],"recent":[220],"work":[221],"VADv2.":[222],"Moreover,":[223],"method":[226],"consumes":[227],"only":[228,250],"44.3%":[229],"resources":[231],"runs":[235],"$3.4\\times$3.4\u00d7":[236],"faster":[237],"inference":[239],"when":[240],"employing":[241],"same":[243],"backbone":[244],"network.":[245],"innovative":[247],"not":[249],"first":[253],"time":[254],"demonstrates":[255],"unarguable":[256],"advantages":[258],"counterparts,":[261],"but":[262],"also":[263],"enjoys":[264],"unprecedented":[265],"efficiency":[266],"data,":[268],"training,":[269]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}
