{"id":"https://openalex.org/W4417052003","doi":"https://doi.org/10.1109/lra.2025.3641130","title":"AttBEV: Enhancing Multi-Modal 3D Object Detection With CBAM Attention in BEVFusion for Autonomous Driving","display_name":"AttBEV: Enhancing Multi-Modal 3D Object Detection With CBAM Attention in BEVFusion for Autonomous Driving","publication_year":2025,"publication_date":"2025-12-05","ids":{"openalex":"https://openalex.org/W4417052003","doi":"https://doi.org/10.1109/lra.2025.3641130"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2025.3641130","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2025.3641130","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/lra.2025.3641130","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Na Zhang","orcid":"https://orcid.org/0009-0005-1764-4341"},"institutions":[{"id":"https://openalex.org/I9617848","display_name":"Universitat Polit\u00e8cnica de Catalunya","ror":"https://ror.org/03mb6wj31","country_code":"ES","type":"education","lineage":["https://openalex.org/I9617848"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Na Zhang","raw_affiliation_strings":["School of Industry Engineering, Polytechnic University of Catalonia Barcelona, Barcelona, Spain"],"raw_orcid":"https://orcid.org/0009-0005-1764-4341","affiliations":[{"raw_affiliation_string":"School of Industry Engineering, Polytechnic University of Catalonia Barcelona, Barcelona, Spain","institution_ids":["https://openalex.org/I9617848"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058448958","display_name":"Edmundo Guerra","orcid":"https://orcid.org/0000-0002-6696-0982"},"institutions":[{"id":"https://openalex.org/I9617848","display_name":"Universitat Polit\u00e8cnica de Catalunya","ror":"https://ror.org/03mb6wj31","country_code":"ES","type":"education","lineage":["https://openalex.org/I9617848"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Edmundo Guerra","raw_affiliation_strings":["School of Industry Engineering, Polytechnic University of Catalonia Barcelona, Barcelona, Spain"],"raw_orcid":"https://orcid.org/0000-0002-6696-0982","affiliations":[{"raw_affiliation_string":"School of Industry Engineering, Polytechnic University of Catalonia Barcelona, Barcelona, Spain","institution_ids":["https://openalex.org/I9617848"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056028210","display_name":"Antoni Grau","orcid":"https://orcid.org/0000-0003-4112-3325"},"institutions":[{"id":"https://openalex.org/I9617848","display_name":"Universitat Polit\u00e8cnica de Catalunya","ror":"https://ror.org/03mb6wj31","country_code":"ES","type":"education","lineage":["https://openalex.org/I9617848"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Antoni Grau","raw_affiliation_strings":["School of Industry Engineering, Polytechnic University of Catalonia Barcelona, Barcelona, Spain"],"raw_orcid":"https://orcid.org/0000-0003-4112-3325","affiliations":[{"raw_affiliation_string":"School of Industry Engineering, Polytechnic University of Catalonia Barcelona, Barcelona, Spain","institution_ids":["https://openalex.org/I9617848"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I9617848"],"apc_list":null,"apc_paid":null,"fwci":0.5236,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70007664,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"11","issue":"2","first_page":"1322","last_page":"1329"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9488000273704529,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9488000273704529,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.011500000022351742,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.004900000058114529,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/object-detection","display_name":"Object detection","score":0.7139999866485596},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5806000232696533},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49219998717308044},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4796000123023987},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4763999879360199},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4672999978065491},{"id":"https://openalex.org/keywords/fusion-mechanism","display_name":"Fusion mechanism","score":0.4142000079154968},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.39640000462532043},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.3944999873638153}],"concepts":[{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7139999866485596},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7099000215530396},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7077999711036682},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6384000182151794},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5806000232696533},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49219998717308044},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4796000123023987},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4763999879360199},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4672999978065491},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.4142000079154968},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.39640000462532043},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32850000262260437},{"id":"https://openalex.org/C2982962833","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information fusion","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2892000079154968},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2888999879360199},{"id":"https://openalex.org/C2988416141","wikidata":"https://www.wikidata.org/wiki/Q6031139","display_name":"Information loss","level":2,"score":0.2865000069141388},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.26919999718666077},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.25839999318122864},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.25380000472068787},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lra.2025.3641130","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2025.3641130","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},{"id":"pmh:oai:upcommons.upc.edu:2117/460404","is_oa":true,"landing_page_url":"https://hdl.handle.net/2117/460404","pdf_url":"https://upcommons.upc.edu/bitstreams/ed3c1e55-1120-4529-8480-9aa23954d13e/download","source":{"id":"https://openalex.org/S4377196262","display_name":"UPCommons institutional repository (Universitat Polit\u00e8cnica de Catalunya)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I9617848","host_organization_name":"Universitat Polit\u00e8cnica de Catalunya","host_organization_lineage":["https://openalex.org/I9617848"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1109/lra.2025.3641130","is_oa":true,"landing_page_url":"https://doi.org/10.1109/lra.2025.3641130","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G619932635","display_name":null,"funder_award_id":"202408440115","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W2752782242","https://openalex.org/W2897529137","https://openalex.org/W2963925437","https://openalex.org/W2968296999","https://openalex.org/W3017930107","https://openalex.org/W3035346742","https://openalex.org/W3035461736","https://openalex.org/W3035574168","https://openalex.org/W3096609285","https://openalex.org/W3107422826","https://openalex.org/W3109395584","https://openalex.org/W3138516171","https://openalex.org/W3166470370","https://openalex.org/W4225793049","https://openalex.org/W4289752563","https://openalex.org/W4310078553","https://openalex.org/W4312617306","https://openalex.org/W4318831014","https://openalex.org/W4383066393","https://openalex.org/W4386075636","https://openalex.org/W4386076457","https://openalex.org/W4390872460"],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"fusion":[1,26,68,77],"has":[2,16],"an":[3,66],"important":[4],"research":[5],"value":[6],"in":[7,31,147,163],"environmental":[8],"perception":[9],"for":[10,23,53],"autonomous":[11,164],"driving.":[12],"Among":[13],"them,":[14],"BEVFusion":[15,115],"become":[17],"one":[18],"of":[19,96,159],"the":[20,32,75,85,104,157],"mainstream":[21],"framework":[22],"LiDAR":[24],"camera":[25],"by":[27,42],"unifying":[28],"multimodal":[29],"features":[30],"bird's-eye":[33],"view":[34],"(BEV)":[35],"space.":[36],"However,":[37],"its":[38],"performance":[39,112,158],"is":[40,124,135],"limited":[41],"inefficient":[43],"cross-modal":[44],"interaction":[45],"and":[46,56,98,130,151,154],"information":[47,91],"loss":[48],"during":[49],"BEV":[50],"projection,":[51],"especially":[52],"dynamic":[54,93],"objects":[55],"edge":[57],"cases.":[58],"To":[59],"address":[60],"these":[61],"limitations,":[62],"we":[63],"propose":[64],"AttBEV,":[65],"advanced":[67],"architecture":[69],"that":[70,83,108],"introduces":[71],"a":[72,79],"CBAM":[73],"at":[74],"feature":[76,94],"layer:":[78],"lightweight":[80],"attention":[81],"mechanism":[82],"improves":[84,156],"model's":[86],"ability":[87,153],"to":[88,114],"capture":[89],"key":[90],"through":[92],"calibration":[95],"channel":[97],"spatial":[99],"dimensions.":[100],"Extensive":[101],"experiments":[102],"on":[103,116],"nuScenes":[105],"dataset":[106],"demonstrate":[107],"AttBEV":[109,143],"achieves":[110],"superior":[111],"compared":[113],"most":[117],"evaluation":[118],"metrics.":[119],"NDS":[120],"reaches":[121,132],"0.6795,":[122],"which":[123,134],"2.63%":[125],"higher":[126,137],"than":[127,138],"BEVFusion's":[128,139],"0.6532,":[129],"mAP":[131],"0.6426,":[133],"1.79%":[136],"0.6247.":[140],"In":[141],"general,":[142],"outperforms":[144],"existing":[145],"methods":[146],"both":[148],"model":[149],"accuracy":[150],"generalization":[152],"significantly":[155],"3D":[160],"object":[161],"detection":[162],"driving":[165],"scenarios.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-02T14:50:37.381335","created_date":"2025-12-05T00:00:00"}
