{"id":"https://openalex.org/W7131118863","doi":"https://doi.org/10.1109/iccvw69036.2025.00564","title":"Hierarchical Multi-Modal Fusion for Roadside VRU Detection: Method Complementarity Under Sparse Label Constraints","display_name":"Hierarchical Multi-Modal Fusion for Roadside VRU Detection: Method Complementarity Under Sparse Label Constraints","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W7131118863","doi":"https://doi.org/10.1109/iccvw69036.2025.00564"},"language":null,"primary_location":{"id":"doi:10.1109/iccvw69036.2025.00564","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00564","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-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/A5001964801","display_name":"Chuheng Wei","orcid":"https://orcid.org/0000-0002-0747-9398"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Chuheng Wei","raw_affiliation_strings":["University of California,Riverside"],"affiliations":[{"raw_affiliation_string":"University of California,Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Ziyan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ziyan Zhang","raw_affiliation_strings":["University of California,Riverside"],"affiliations":[{"raw_affiliation_string":"University of California,Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102737567","display_name":"Haishan Liu","orcid":"https://orcid.org/0000-0002-0817-9928"},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Haishan Liu","raw_affiliation_strings":["University of California,Riverside"],"affiliations":[{"raw_affiliation_string":"University of California,Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019165513","display_name":"Guoyuan Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoyuan Wu","raw_affiliation_strings":["University of California,Riverside"],"affiliations":[{"raw_affiliation_string":"University of California,Riverside","institution_ids":["https://openalex.org/I103635307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126588457","display_name":"Matthew J. Barth","orcid":null},"institutions":[{"id":"https://openalex.org/I103635307","display_name":"University of California, Riverside","ror":"https://ror.org/03nawhv43","country_code":"US","type":"education","lineage":["https://openalex.org/I103635307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew J. Barth","raw_affiliation_strings":["University of California,Riverside"],"affiliations":[{"raw_affiliation_string":"University of California,Riverside","institution_ids":["https://openalex.org/I103635307"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5001964801"],"corresponding_institution_ids":["https://openalex.org/I103635307"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.59945497,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5402","last_page":"5409"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.37130001187324524,"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":0.37130001187324524,"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":0.33309999108314514,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.0860000029206276,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/robustness","display_name":"Robustness (evolution)","score":0.6539999842643738},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.6305000185966492},{"id":"https://openalex.org/keywords/complementarity","display_name":"Complementarity (molecular biology)","score":0.5860000252723694},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4925999939441681},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.492000013589859},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47360000014305115},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.44670000672340393}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7028999924659729},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6539999842643738},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.6305000185966492},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5867000222206116},{"id":"https://openalex.org/C202269582","wikidata":"https://www.wikidata.org/wiki/Q2644277","display_name":"Complementarity (molecular biology)","level":2,"score":0.5860000252723694},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4925999939441681},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.492000013589859},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47360000014305115},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45159998536109924},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.44670000672340393},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4163999855518341},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38920000195503235},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.37950000166893005},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.30480000376701355},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.2802000045776367},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.26010000705718994}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccvw69036.2025.00564","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccvw69036.2025.00564","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2008056655","https://openalex.org/W2031454541","https://openalex.org/W2088173505","https://openalex.org/W2555618208","https://openalex.org/W2560674596","https://openalex.org/W2897529137","https://openalex.org/W2900279443","https://openalex.org/W2902068467","https://openalex.org/W2911964244","https://openalex.org/W2914625278","https://openalex.org/W2962783540","https://openalex.org/W2963070905","https://openalex.org/W2963727135","https://openalex.org/W2964062501","https://openalex.org/W2964115968","https://openalex.org/W2968296999","https://openalex.org/W2968634921","https://openalex.org/W3035461736","https://openalex.org/W3043157863","https://openalex.org/W3096609285","https://openalex.org/W3118508671","https://openalex.org/W3130463448","https://openalex.org/W3135991645","https://openalex.org/W3164576087","https://openalex.org/W3169708801","https://openalex.org/W4213450898","https://openalex.org/W4214724741","https://openalex.org/W4285606661","https://openalex.org/W4312502508","https://openalex.org/W4312559104","https://openalex.org/W4312976258","https://openalex.org/W4315631841","https://openalex.org/W4382466690","https://openalex.org/W4383066393","https://openalex.org/W4386083048","https://openalex.org/W4387618341","https://openalex.org/W4402916119","https://openalex.org/W4408697117","https://openalex.org/W4409033501","https://openalex.org/W4413018770"],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"detection":[1,36,49,114,149,167],"of":[2,47,90,96,135],"Vulnerable":[3],"Road":[4],"Users":[5],"(VRUs)":[6],"by":[7],"roadside":[8],"sensors":[9],"poses":[10],"significant":[11],"challenges":[12],"due":[13],"to":[14,99],"sparse":[15],"labeled":[16],"data":[17],"and":[18,71,104,118,139],"multimodal":[19,28],"sensor":[20],"fusion":[21,29,129],"complexity.":[22],"This":[23],"paper":[24],"proposes":[25],"a":[26,56],"hierarchical":[27,128],"framework":[30,61],"that":[31],"integrates":[32],"traditional":[33,67,136],"3D":[34,68],"object":[35],"methods":[37,103],"with":[38,51,93],"deep":[39,107,140],"learning-based":[40],"approaches.":[41,109],"Our":[42,127],"method":[43,150],"combines":[44],"the":[45,81,88,155],"robustness":[46],"conventional":[48,102],"pipelines":[50],"neural":[52],"network":[53],"adaptability":[54],"through":[55,75],"novel":[57],"complementarity":[58],"strategy.":[59],"The":[60,144],"employs":[62],"DAB-DETR":[63],"for":[64,101,106,122,163],"2D":[65],"detection,":[66,120],"clustering":[69],"algorithms,":[70],"PointPillars":[72],"architecture,":[73],"unified":[74],"confidence-based":[76],"fusion.":[77],"Experimental":[78],"evaluation":[79],"on":[80,147],"Intersection":[82],"Safety":[83],"Challenge":[84],"(ISC)":[85],"dataset":[86],"demonstrates":[87],"effectiveness":[89,162],"our":[91],"approach":[92],"overall":[94],"mAP@0.5":[95],"49.12%":[97],"compared":[98],"36%":[100],"15.99%":[105],"learning":[108,141],"Notable":[110],"improvements":[111],"include":[112],"vehicle":[113],"(46.09%":[115],"vs.":[116,125],"39.12%)":[117],"VRU":[119,166],"especially":[121],"children":[123],"(30.71%":[124],"3.61%).":[126],"strategy":[130],"successfully":[131],"leverages":[132],"complementary":[133],"strengths":[134],"classification":[137],"accuracy":[138],"localization":[142],"precision.":[143],"solution":[145],"based":[146],"this":[148],"won":[151],"an":[152],"award":[153],"in":[154],"ISC":[156],"Stage":[157],"1B":[158],"competition,":[159],"validating":[160],"its":[161],"data-constrained":[164],"road-side":[165],"scenarios.":[168]},"counts_by_year":[],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2026-02-24T00:00:00"}
