{"id":"https://openalex.org/W4388198076","doi":"https://doi.org/10.3390/s23218732","title":"Multiattention Mechanism 3D Object Detection Algorithm Based on RGB and LiDAR Fusion for Intelligent Driving","display_name":"Multiattention Mechanism 3D Object Detection Algorithm Based on RGB and LiDAR Fusion for Intelligent Driving","publication_year":2023,"publication_date":"2023-10-26","ids":{"openalex":"https://openalex.org/W4388198076","doi":"https://doi.org/10.3390/s23218732","pmid":"https://pubmed.ncbi.nlm.nih.gov/37960432"},"language":"en","primary_location":{"id":"doi:10.3390/s23218732","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218732","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8732/pdf?version=1698306265","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/21/8732/pdf?version=1698306265","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101662425","display_name":"Xiucai Zhang","orcid":"https://orcid.org/0009-0000-3674-4018"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiucai Zhang","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108848416","display_name":"Lei He","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lei He","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038050410","display_name":"Junyi Chen","orcid":"https://orcid.org/0000-0003-0789-9445"},"institutions":[{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]},{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyi Chen","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035382300","display_name":"Baoyun Wang","orcid":"https://orcid.org/0000-0002-7784-5605"},"institutions":[{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]},{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoyun Wang","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100622297","display_name":"Yuhai Wang","orcid":"https://orcid.org/0000-0002-8251-7948"},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhai Wang","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113036802","display_name":"Yuanle Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I194450716","display_name":"Jilin University","ror":"https://ror.org/00js3aw79","country_code":"CN","type":"education","lineage":["https://openalex.org/I194450716"]},{"id":"https://openalex.org/I4392738231","display_name":"State Key Laboratory of Automotive Simulation and Control","ror":"https://ror.org/00b67z867","country_code":null,"type":"facility","lineage":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanle Zhou","raw_affiliation_strings":["State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China","institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5108848416"],"corresponding_institution_ids":["https://openalex.org/I194450716","https://openalex.org/I4392738231"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":0.8558,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.76040292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"23","issue":"21","first_page":"8732","last_page":"8732"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9912999868392944,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8418052196502686},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.7508296966552734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.734383761882782},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.71385258436203},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6194231510162354},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.6014657616615295},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5653591752052307},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5551370978355408},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5432999134063721},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5020925998687744},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4747225046157837},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45272496342658997},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.43134230375289917},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42692044377326965},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.404674232006073},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.144550621509552}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8418052196502686},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.7508296966552734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.734383761882782},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.71385258436203},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6194231510162354},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.6014657616615295},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5653591752052307},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5551370978355408},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5432999134063721},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5020925998687744},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4747225046157837},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45272496342658997},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.43134230375289917},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42692044377326965},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.404674232006073},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.144550621509552},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/s23218732","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218732","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8732/pdf?version=1698306265","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:37960432","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37960432","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10649988","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10649988","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10649988/pdf/sensors-23-08732.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:5fcf5e447b02404592b7372771701fd6","is_oa":true,"landing_page_url":"https://doaj.org/article/5fcf5e447b02404592b7372771701fd6","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 21, p 8732 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s23218732","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23218732","pdf_url":"https://www.mdpi.com/1424-8220/23/21/8732/pdf?version=1698306265","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4388198076.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W49218792","https://openalex.org/W1519128923","https://openalex.org/W1522734439","https://openalex.org/W1536680647","https://openalex.org/W1563354748","https://openalex.org/W1596717185","https://openalex.org/W1861492603","https://openalex.org/W1946609740","https://openalex.org/W1966456026","https://openalex.org/W1978736542","https://openalex.org/W2011792403","https://openalex.org/W2162411291","https://openalex.org/W2194775991","https://openalex.org/W2229637417","https://openalex.org/W2468368736","https://openalex.org/W2555254696","https://openalex.org/W2555618208","https://openalex.org/W2558294288","https://openalex.org/W2560544142","https://openalex.org/W2570343428","https://openalex.org/W2595840341","https://openalex.org/W2605189827","https://openalex.org/W2798965597","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2954174912","https://openalex.org/W2962807143","https://openalex.org/W2963037989","https://openalex.org/W2963083779","https://openalex.org/W2963351448","https://openalex.org/W2963400571","https://openalex.org/W2963721253","https://openalex.org/W2963727135","https://openalex.org/W2964062501","https://openalex.org/W2964166085","https://openalex.org/W2968296999","https://openalex.org/W2969808474","https://openalex.org/W2972211064","https://openalex.org/W2997814983","https://openalex.org/W3004237909","https://openalex.org/W3034602892","https://openalex.org/W3035461736","https://openalex.org/W3117804044","https://openalex.org/W3213561510","https://openalex.org/W4281390486","https://openalex.org/W6696987079"],"related_works":["https://openalex.org/W3027020613","https://openalex.org/W2016533837","https://openalex.org/W3167885074","https://openalex.org/W2892386716","https://openalex.org/W4306164210","https://openalex.org/W1998563493","https://openalex.org/W4313316311","https://openalex.org/W4362608745","https://openalex.org/W2082728368","https://openalex.org/W2383143032"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,95],"multimodal":[4],"fusion":[5,65,77,80,92],"3D":[6,20,133,178],"target":[7,21],"detection":[8],"algorithm":[9,24,118,165],"based":[10],"on":[11],"the":[12,17,32,38,53,85,104,113,116,120,126,132,159,163,171,177],"attention":[13,89],"mechanism":[14],"to":[15,58,112,181],"improve":[16],"performance":[18,100],"of":[19,66,162],"detection.":[22],"The":[23,64,98,107],"utilizes":[25],"point":[26,60,69,76],"cloud":[27,49,70],"data":[28],"and":[29,56,61,68,78,87,129,140,145,152,157,174],"information":[30,83],"from":[31],"camera.":[33],"For":[34],"image":[35,67],"feature":[36,50],"extraction,":[37],"ResNet50":[39],"+":[40],"FPN":[41],"architecture":[42],"extracts":[43],"features":[44,71,93],"at":[45,94,135],"four":[46],"levels.":[47],"Point":[48],"extraction":[51],"employs":[52],"voxel":[54,62,79],"method":[55],"FCN":[57],"extract":[59,91],"features.":[63],"is":[72,101,166],"achieved":[73],"through":[74],"regional":[75],"methods.":[81],"After":[82],"fusion,":[84],"Coordinate":[86],"SimAM":[88],"mechanisms":[90],"deep":[96],"level.":[97],"algorithm's":[99],"evaluated":[102],"using":[103],"DAIR-V2X":[105],"dataset.":[106],"results":[108],"show":[109],"that":[110],"compared":[111,180],"Part-A2":[114],"algorithm;":[115],"proposed":[117],"improves":[119],"mAP":[121,160],"value":[122,161],"by":[123,168],"7.9%":[124],"in":[125,131,170,176],"BEV":[127,172],"view":[128,134,173],"7.8%":[130],"IOU":[136,141,148,153],"=":[137,142,149,154],"0.5":[138,155],"(cars)":[139,151],"0.25":[143],"(pedestrians":[144,156],"cyclists).":[146],"At":[147],"0.7":[150],"cyclists),":[158],"SECOND":[164],"improved":[167],"5.4%":[169],"4.3%":[175],"view,":[179],"other":[182],"comparison":[183],"algorithms.":[184]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
