{"id":"https://openalex.org/W4414322148","doi":"https://doi.org/10.1109/access.2025.3611412","title":"A Hybrid Network of CNN and Transformer for 3D Lane Detection","display_name":"A Hybrid Network of CNN and Transformer for 3D Lane Detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414322148","doi":"https://doi.org/10.1109/access.2025.3611412"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3611412","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3611412","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3611412","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111290675","display_name":"Yifan Deng","orcid":"https://orcid.org/0009-0003-5595-3001"},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanyang Deng","raw_affiliation_strings":["Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0003-5595-3001","affiliations":[{"raw_affiliation_string":"Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I51622183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103087633","display_name":"Mingwei Wang","orcid":"https://orcid.org/0000-0001-9285-9071"},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingwei Wang","raw_affiliation_strings":["Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0000-0001-9285-9071","affiliations":[{"raw_affiliation_string":"Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I51622183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102964557","display_name":"Mengli Zhang","orcid":"https://orcid.org/0009-0004-6348-3174"},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengli Zhang","raw_affiliation_strings":["Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0004-6348-3174","affiliations":[{"raw_affiliation_string":"Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I51622183"]}]},{"author_position":"last","author":{"id":null,"display_name":"Menglu Zhou","orcid":"https://orcid.org/0009-0003-1190-2878"},"institutions":[{"id":"https://openalex.org/I51622183","display_name":"Shaanxi University of Science and Technology","ror":"https://ror.org/034t3zs45","country_code":"CN","type":"education","lineage":["https://openalex.org/I51622183"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Menglu Zhou","raw_affiliation_strings":["Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China"],"raw_orcid":"https://orcid.org/0009-0003-1190-2878","affiliations":[{"raw_affiliation_string":"Shaanxi Joint Laboratory of Artificial Intelligence, Shaanxi University of Science and Technology, Xi’an, China","institution_ids":["https://openalex.org/I51622183"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5111290675"],"corresponding_institution_ids":["https://openalex.org/I51622183"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.25682228,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"164237","last_page":"164248"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9930999875068665,"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":0.9930999875068665,"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":0.9602000117301941,"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/T10320","display_name":"Neural Networks and Applications","score":0.9589999914169312,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/transformer","display_name":"Transformer","score":0.6383000016212463},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6309999823570251},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4569999873638153},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4074000120162964},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.4056999981403351},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39629998803138733},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.34709998965263367},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.32760000228881836}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8292999863624573},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6383000016212463},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6309999823570251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6187000274658203},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4569999873638153},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4074000120162964},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39629998803138733},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.359499990940094},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.34709998965263367},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.32760000228881836},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3167000114917755},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C2779990667","wikidata":"https://www.wikidata.org/wiki/Q5953266","display_name":"Hybrid neural network","level":3,"score":0.28299999237060547},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2782999873161316},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.25760000944137573},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.25360000133514404},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2526000142097473}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3611412","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3611412","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:da11c4f54f2e4c1c8cad5891a1bb11e7","is_oa":true,"landing_page_url":"https://doaj.org/article/da11c4f54f2e4c1c8cad5891a1bb11e7","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 164237-164248 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3611412","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3611412","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4650213405","display_name":null,"funder_award_id":"2024QCY-KXJ-181","funder_id":"https://openalex.org/F4320327224","funder_display_name":"Shaanxi Provincial Science and Technology Department"}],"funders":[{"id":"https://openalex.org/F4320327224","display_name":"Shaanxi Provincial Science and Technology Department","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1968256263","https://openalex.org/W2095905764","https://openalex.org/W2152422345","https://openalex.org/W2194775991","https://openalex.org/W2780740184","https://openalex.org/W2913960518","https://openalex.org/W2963840672","https://openalex.org/W2964199920","https://openalex.org/W2989279786","https://openalex.org/W2995724453","https://openalex.org/W3014005442","https://openalex.org/W3035414587","https://openalex.org/W3119586106","https://openalex.org/W3138516171","https://openalex.org/W3173721678","https://openalex.org/W3173771298","https://openalex.org/W3175091786","https://openalex.org/W3176566042","https://openalex.org/W4221143432","https://openalex.org/W4226493478","https://openalex.org/W4289752563","https://openalex.org/W4312603285","https://openalex.org/W4312604822","https://openalex.org/W4312713480","https://openalex.org/W4312807693","https://openalex.org/W4312839759","https://openalex.org/W4312847199","https://openalex.org/W4312894406","https://openalex.org/W4382464460","https://openalex.org/W4383108583","https://openalex.org/W4385245566","https://openalex.org/W4385764464","https://openalex.org/W4386066269","https://openalex.org/W4386076601","https://openalex.org/W4387199878","https://openalex.org/W4390872779","https://openalex.org/W4392904456","https://openalex.org/W4393156413","https://openalex.org/W4394828291","https://openalex.org/W4395056572","https://openalex.org/W4401210645","https://openalex.org/W4402754159","https://openalex.org/W4409365419"],"related_works":[],"abstract_inverted_index":{"3D":[0,80],"lane":[1,22,46,81],"detection":[2,82,158],"is":[3],"a":[4,35,79,101,119,140],"critical":[5],"and":[6,18,88,95,129,131,148,164,184],"challenging":[7,25],"task":[8],"in":[9,26,70],"autonomous":[10],"driving,":[11],"yet":[12],"accurately":[13],"capturing":[14],"the":[15,62,123,132,162],"spatial":[16,146],"structure":[17],"precise":[19],"location":[20],"of":[21,39,64],"markings":[23],"remains":[24],"complex":[27,178],"traffic":[28],"environments.":[29],"Existing":[30],"methods":[31,175],"typically":[32],"rely":[33],"on":[34,106,161],"single":[36],"network":[37],"architecture":[38],"Convolutional":[40],"Neural":[41],"Networks(CNNs)":[42],"or":[43],"Transformer":[44,89,133],"for":[45],"detection,":[47],"CNNs":[48,87],"captures":[49,135],"local":[50,66,94],"details":[51],"but":[52],"lacks":[53],"long-range":[54],"context,":[55],"while":[56],"Transformers":[57],"extract":[58],"global":[59,96,136],"semantics":[60],"at":[61],"expense":[63],"fine":[65,127],"detail,":[67],"often":[68],"resulting":[69],"imprecise":[71],"localization.":[72],"To":[73],"overcome":[74],"these":[75,154],"limitations,":[76],"we":[77,99,117],"propose":[78],"framework":[83],"that":[84,168],"integrates":[85],"both":[86],"architectures":[90],"to":[91,109,156],"simultaneously":[92],"harness":[93],"information.":[97],"Specifically,":[98],"introduce":[100],"view":[102,112],"transformation":[103],"module":[104,143],"based":[105],"Spatial":[107],"Cross-Attention":[108],"optimize":[110],"bird’s-eye":[111],"(BEV)":[113],"feature":[114,141],"representation.":[115],"Then":[116],"designed":[118],"Dual-Branch":[120],"network,":[121],"where":[122],"CNN":[124],"branch":[125,134],"extracts":[126],"textures":[128],"edges,":[130],"semantic":[137],"relationships.":[138],"Finally,":[139],"fusion":[142],"(FFM)":[144],"combining":[145],"attention":[147,150],"channel":[149],"mechanisms":[151],"dynamically":[152],"merges":[153],"features":[155],"enhance":[157],"performance.":[159],"Experiments":[160],"OpenLane":[163],"Apollo":[165],"datasets":[166],"show":[167],"our":[169],"approach":[170],"significantly":[171],"outperforms":[172],"current":[173],"advanced":[174],"under":[176],"various":[177],"road":[179],"conditions,":[180],"demonstrating":[181],"its":[182],"effectiveness":[183],"generalizability.":[185]},"counts_by_year":[],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}