{"id":"https://openalex.org/W4412567545","doi":"https://doi.org/10.1109/tgrs.2025.3591489","title":"VPDNet: Virtual Point Density-Aware Network for Multimodal 3-D Object Detection","display_name":"VPDNet: Virtual Point Density-Aware Network for Multimodal 3-D Object Detection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4412567545","doi":"https://doi.org/10.1109/tgrs.2025.3591489"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3591489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3591489","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5043100857","display_name":"Binghui Yang","orcid":"https://orcid.org/0009-0007-6674-1134"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Binghui Yang","raw_affiliation_strings":["School of Electronic information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100401503","display_name":"Tao Tao","orcid":"https://orcid.org/0000-0002-7333-7953"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Tao","raw_affiliation_strings":["School of Electronic information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034580864","display_name":"Jianfeng Yang","orcid":"https://orcid.org/0000-0003-2002-9073"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianfeng Yang","raw_affiliation_strings":["School of Electronic information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085306541","display_name":"Jinsheng Xiao","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinsheng Xiao","raw_affiliation_strings":["School of Electronic information, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5043100857"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":2.1813,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.87525663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9771000146865845,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9771000146865845,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9656000137329102,"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":0.9556999802589417,"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/computer-science","display_name":"Computer science","score":0.753726601600647},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5580819249153137},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.504428505897522},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4998898506164551},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.49151191115379333},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45841217041015625},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3308802843093872},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2805137634277344},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.10839992761611938}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.753726601600647},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5580819249153137},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.504428505897522},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4998898506164551},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.49151191115379333},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45841217041015625},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3308802843093872},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2805137634277344},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.10839992761611938},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3591489","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3591489","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8313380188","display_name":null,"funder_award_id":"2022BCA035","funder_id":"https://openalex.org/F4320330214","funder_display_name":"Key Research and Development Program of Hunan Province of China"}],"funders":[{"id":"https://openalex.org/F4320330214","display_name":"Key Research and Development Program of Hunan Province of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2555618208","https://openalex.org/W2560609797","https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2954174912","https://openalex.org/W2963400571","https://openalex.org/W2963727135","https://openalex.org/W2964062501","https://openalex.org/W2967324759","https://openalex.org/W2968296999","https://openalex.org/W2981949127","https://openalex.org/W3017930107","https://openalex.org/W3034314779","https://openalex.org/W3034402935","https://openalex.org/W3034407526","https://openalex.org/W3034602892","https://openalex.org/W3035461736","https://openalex.org/W3109395584","https://openalex.org/W3118341329","https://openalex.org/W3130463448","https://openalex.org/W3205005447","https://openalex.org/W3206335707","https://openalex.org/W3217335336","https://openalex.org/W4200632008","https://openalex.org/W4293577719","https://openalex.org/W4293811845","https://openalex.org/W4312437143","https://openalex.org/W4313158203","https://openalex.org/W4367182782","https://openalex.org/W4378696925","https://openalex.org/W4386071826","https://openalex.org/W4386075854","https://openalex.org/W4386083121","https://openalex.org/W6739778489","https://openalex.org/W6769571200"],"related_works":["https://openalex.org/W2121524756","https://openalex.org/W782553550","https://openalex.org/W1987967678","https://openalex.org/W2633218168","https://openalex.org/W4235897794","https://openalex.org/W2737719445","https://openalex.org/W2059707233","https://openalex.org/W1983126463","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Lidar":[0,25,158],"has":[1],"become":[2],"a":[3,60,94,181],"prevalent":[4],"sensor":[5],"for":[6],"3D":[7,64,212],"object":[8,31,65,213],"detection":[9,32,36,66,214,218],"in":[10],"autonomous":[11],"driving.":[12],"However,":[13],"the":[14,27,41,78,85,155,205,224],"sparse":[15],"and":[16,38,47,69,129,146,169,193],"irregular":[17],"nature":[18],"of":[19,29,44,80,105,157],"point":[20,45,74,96,107,130,144,148,162,170,194],"cloud":[21,97,163],"data":[22,51,81,164],"obtained":[23],"from":[24,127,142],"necessitates":[26],"adoption":[28],"cross-modal":[30],"methods":[33],"to":[34,54,76,114,123,197,223],"enhance":[35],"accuracy":[37],"stability.":[39],"Nonetheless,":[40],"disparate":[42],"representations":[43],"clouds":[46,75,108,145,149],"images":[48,128],"hinder":[49],"comprehensive":[50],"fusion,":[52],"leading":[53],"suboptimal":[55],"performance.":[56],"This":[57,100],"paper":[58],"proposes":[59],"novel":[61],"multimodal":[62],"density-aware":[63,182],"method,":[67],"VPDNet,":[68],"leverages":[70],"depth":[71,90],"completion-generated":[72],"virtual":[73,95,106,143],"address":[77],"challenges":[79],"fusion.":[82],"To":[83],"mitigate":[84],"interference":[86],"caused":[87],"by":[88,150,220],"inaccurate":[89],"completion,":[91],"we":[92,132,179],"introduce":[93],"enhancement":[98],"module.":[99],"module":[101,138,183],"utilizes":[102],"weighted":[103],"features":[104,141,188],"based":[109],"on":[110,204],"image":[111],"segmentation":[112],"information":[113,117,126,196],"suppress":[115],"invalid":[116],"while":[118],"retaining":[119],"valid":[120],"information.":[121],"Furthermore,":[122],"further":[124],"capture":[125],"clouds,":[131],"design":[133],"an":[134,172],"interactive":[135],"attention":[136,152],"fusion":[137],"that":[139,160,184,209],"integrates":[140],"real":[147],"adjusting":[151],"weights.":[153],"Additionally,":[154],"characteristics":[156],"dictate":[159],"collected":[161],"varies":[165],"unevenly":[166],"with":[167,189],"distance,":[168],"density,":[171],"essential":[173],"feature,":[174],"is":[175,229],"often":[176],"overlooked.":[177],"Therefore,":[178],"propose":[180],"combines":[185],"fused":[186],"voxel":[187],"kernel":[190],"density":[191,195],"estimation":[192],"extract":[198],"spatial":[199],"local":[200],"features.":[201],"Experiments":[202],"conducted":[203],"KITTI":[206],"dataset":[207],"demonstrate":[208],"our":[210],"proposed":[211],"algorithm":[215],"improves":[216],"pedestrian":[217],"results":[219],"6.93%":[221],"compared":[222],"baseline":[225],"network.":[226],"The":[227],"code":[228],"available":[230],"at":[231],"https://github.com/Alexandriahui/VPDNet.":[232]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-14T08:04:32.555800","created_date":"2025-10-10T00:00:00"}
