{"id":"https://openalex.org/W4400447268","doi":"https://doi.org/10.1109/tits.2024.3420432","title":"TransFusion: Multi-Modal Robust Fusion for 3D Object Detection in Foggy Weather Based on Spatial Vision Transformer","display_name":"TransFusion: Multi-Modal Robust Fusion for 3D Object Detection in Foggy Weather Based on Spatial Vision Transformer","publication_year":2024,"publication_date":"2024-07-09","ids":{"openalex":"https://openalex.org/W4400447268","doi":"https://doi.org/10.1109/tits.2024.3420432"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2024.3420432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3420432","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/A5024451053","display_name":"Cheng Zhang","orcid":"https://orcid.org/0000-0001-6322-9783"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cheng Zhang","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100771674","display_name":"Hai Wang","orcid":"https://orcid.org/0000-0002-9136-8091"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai Wang","raw_affiliation_strings":["School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057276700","display_name":"Yingfeng Cai","orcid":"https://orcid.org/0000-0002-0633-9887"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingfeng Cai","raw_affiliation_strings":["Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100630554","display_name":"Long Chen","orcid":"https://orcid.org/0000-0002-2079-3867"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Long Chen","raw_affiliation_strings":["Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100657987","display_name":"Yicheng Li","orcid":"https://orcid.org/0000-0003-2937-7162"},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yicheng Li","raw_affiliation_strings":["Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China"],"affiliations":[{"raw_affiliation_string":"Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5024451053"],"corresponding_institution_ids":["https://openalex.org/I115592961"],"apc_list":null,"apc_paid":null,"fwci":2.9399,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.92246463,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"25","issue":"9","first_page":"10652","last_page":"10666"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994999766349792,"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":0.9994999766349792,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996399998664856,"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/modal","display_name":"Modal","score":0.5600223541259766},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5285008549690247},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5175082683563232},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5085917711257935},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5082123279571533},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4679003953933716},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4603630602359772},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4337160587310791},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.37720948457717896},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.26909708976745605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.235931396484375},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2185664176940918},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.10573816299438477},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.08418196439743042}],"concepts":[{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5600223541259766},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5285008549690247},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5175082683563232},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5085917711257935},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5082123279571533},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4679003953933716},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4603630602359772},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4337160587310791},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.37720948457717896},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.26909708976745605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.235931396484375},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2185664176940918},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.10573816299438477},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.08418196439743042},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2024.3420432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2024.3420432","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":[{"display_name":"Climate action","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G3283955804","display_name":null,"funder_award_id":"U20A20333","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G353827121","display_name":null,"funder_award_id":"52072160","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4011362519","display_name":null,"funder_award_id":"BE2020083-3","funder_id":"https://openalex.org/F4320330214","funder_display_name":"Key Research and Development Program of Hunan Province of China"},{"id":"https://openalex.org/G7909332369","display_name":null,"funder_award_id":"52225212","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320330214","display_name":"Key Research and Development Program of Hunan Province of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W2555618208","https://openalex.org/W2613524681","https://openalex.org/W2798965597","https://openalex.org/W2807096024","https://openalex.org/W2897529137","https://openalex.org/W2911486422","https://openalex.org/W2949708697","https://openalex.org/W2951517617","https://openalex.org/W2962807143","https://openalex.org/W2964062501","https://openalex.org/W2967324759","https://openalex.org/W2968296999","https://openalex.org/W2995057279","https://openalex.org/W3004237909","https://openalex.org/W3007191641","https://openalex.org/W3008115128","https://openalex.org/W3017930107","https://openalex.org/W3034543232","https://openalex.org/W3035346742","https://openalex.org/W3035461736","https://openalex.org/W3035651586","https://openalex.org/W3056795521","https://openalex.org/W3090139470","https://openalex.org/W3091619233","https://openalex.org/W3107819843","https://openalex.org/W3108426750","https://openalex.org/W3118341329","https://openalex.org/W3130463448","https://openalex.org/W3138516171","https://openalex.org/W3139633126","https://openalex.org/W3167095230","https://openalex.org/W3167214600","https://openalex.org/W3167732492","https://openalex.org/W3170030651","https://openalex.org/W3170984066","https://openalex.org/W3186789454","https://openalex.org/W3187263517","https://openalex.org/W3203701986","https://openalex.org/W3209236887","https://openalex.org/W4214493665","https://openalex.org/W4214648293","https://openalex.org/W4214777292","https://openalex.org/W4225535860","https://openalex.org/W4287682901","https://openalex.org/W4287684819","https://openalex.org/W6782015440","https://openalex.org/W6782246188","https://openalex.org/W6783047433","https://openalex.org/W6810594259"],"related_works":["https://openalex.org/W2379392295","https://openalex.org/W3160965418","https://openalex.org/W613940353","https://openalex.org/W2320915480","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W2152662039"],"abstract_inverted_index":{"A":[0],"practical":[1],"approach":[2],"to":[3,13,72,79,88,120,162,182,198],"realizing":[4],"the":[5,9,29,52,59,62,122,160,164,167,184,190,201,204,221,237],"comprehensive":[6],"perception":[7,126],"of":[8,23,54,124,135,166,203],"surrounding":[10],"environment":[11,125],"is":[12,56,77,98,133,180,196,249],"use":[14],"a":[15,107],"multi-modal":[16],"fusion":[17,119],"method":[18],"based":[19],"on":[20,210],"various":[21],"types":[22],"vehicular":[24],"sensors.":[25],"In":[26,188],"clear":[27,231],"weather,":[28,51,236],"camera":[30],"and":[31,37,67,90,97,117,142,152,230],"LiDAR":[32,116],"can":[33,41],"provide":[34],"high-resolution":[35],"images":[36,66],"point":[38,68],"clouds":[39,69],"that":[40,220],"be":[42],"utilized":[43],"for":[44],"3D":[45],"object":[46],"detection.":[47],"However,":[48],"in":[49,61,83,127,159,169,178,227,234],"foggy":[50,128,170,229,235],"propagation":[53],"light":[55],"affected":[57,100],"by":[58,101],"fog":[60],"air.":[63],"Consequently,":[64],"both":[65,228],"become":[70],"distorted":[71],"varying":[73],"degrees.":[74],"Thus,":[75],"it":[76],"challenging":[78],"implement":[80],"accurate":[81],"detection":[82,110],"adverse":[84],"weather":[85],"conditions.":[86],"Compared":[87],"cameras":[89],"LiDAR,":[91],"Radar":[92,118,212],"possesses":[93],"strong":[94],"penetrating":[95],"power":[96],"not":[99],"fog.":[102],"Therefore,":[103],"this":[104],"paper":[105],"proposes":[106],"novel":[108],"two-stage":[109],"framework":[111,132],"called":[112],"\u201cTransFusion\u201d,":[113],"which":[114],"leverages":[115],"solve":[121],"problem":[123],"weather.":[129,171,232],"The":[130,216,247],"proposed":[131,222,238],"composed":[134],"Multi-modal":[136,143],"Rotate":[137],"Region":[138],"Proposal":[139],"Network":[140,145],"(MM-RRPN)":[141],"Refine":[144],"(MM-RFN).":[146],"Specifically,":[147],"Spatial":[148],"Vision":[149],"Transformer":[150],"(SVT)":[151],"Cross-Modal":[153],"Attention":[154],"Mechanism":[155],"(CMAM)":[156],"are":[157],"introduced":[158],"MM-RRPN":[161],"improve":[163],"robustness":[165],"algorithm":[168,223],"Furthermore,":[172],"Temporal-Spatial":[173],"Memory":[174],"Fusion":[175],"(TSMF)":[176],"module":[177],"MM-RFN":[179],"employed":[181],"fuse":[183],"spatial-temporal":[185],"prior":[186],"information.":[187],"addition,":[189],"Multi-branches":[191],"Combination":[192],"Loss":[193],"function":[194],"(MC-Loss)":[195],"designed":[197],"efficiently":[199],"supervise":[200],"learning":[202],"network.":[205],"Extensive":[206],"experiments":[207],"were":[208],"conducted":[209],"Oxford":[211],"RobotCar":[213],"(ORR)":[214],"dataset.":[215],"experimental":[217],"results":[218],"show":[219],"has":[224],"excellent":[225],"performance":[226],"Especially":[233],"TransFusion":[239],"achieves":[240],"85.31mAP,":[241],"outperforming":[242],"all":[243],"other":[244],"competing":[245],"approaches.":[246],"demo":[248],"available":[250],"at:":[251],"<uri":[252],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[253],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://youtu.be/</uri>":[254],"ugjIYHLgn98.":[255]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":2}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}