{"id":"https://openalex.org/W4414556809","doi":"https://doi.org/10.3390/info16100832","title":"Boosting LiDAR Point Cloud Object Detection via Global Feature Fusion","display_name":"Boosting LiDAR Point Cloud Object Detection via Global Feature Fusion","publication_year":2025,"publication_date":"2025-09-26","ids":{"openalex":"https://openalex.org/W4414556809","doi":"https://doi.org/10.3390/info16100832"},"language":"en","primary_location":{"id":"doi:10.3390/info16100832","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16100832","pdf_url":"https://www.mdpi.com/2078-2489/16/10/832/pdf?version=1758884256","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"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":"Information","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2078-2489/16/10/832/pdf?version=1758884256","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100437181","display_name":"Xu Zhang","orcid":"https://orcid.org/0000-0001-8481-0059"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Zhang","raw_affiliation_strings":["School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031613403","display_name":"Fang Tian","orcid":"https://orcid.org/0000-0003-4635-3074"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fengchang Tian","raw_affiliation_strings":["School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101728762","display_name":"Jiaxing Sun","orcid":"https://orcid.org/0000-0002-0170-526X"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaxing Sun","raw_affiliation_strings":["School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I23171815"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101605778","display_name":"Yan Liu","orcid":"https://orcid.org/0000-0002-2471-2112"},"institutions":[{"id":"https://openalex.org/I23171815","display_name":"Zhengzhou University of Light Industry","ror":"https://ror.org/05fwr8z16","country_code":"CN","type":"education","lineage":["https://openalex.org/I23171815"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Liu","raw_affiliation_strings":["School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Zhengzhou University of Light Industry, Zhengzhou 450000, China","institution_ids":["https://openalex.org/I23171815"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101605778"],"corresponding_institution_ids":["https://openalex.org/I23171815"],"apc_list":{"value":1400,"currency":"CHF","value_usd":1515},"apc_paid":{"value":1400,"currency":"CHF","value_usd":1515},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22870359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"16","issue":"10","first_page":"832","last_page":"832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.998199999332428,"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":0.998199999332428,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9980000257492065,"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"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9937999844551086,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8424999713897705},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6571000218391418},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.597599983215332},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5702999830245972},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5383999943733215},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4927999973297119},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.4903999865055084},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4690000116825104}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8424999713897705},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7138000130653381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.695900022983551},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6571000218391418},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6103000044822693},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.597599983215332},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5702999830245972},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5383999943733215},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4927999973297119},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4903999865055084},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.4657000005245209},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.4424999952316284},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.43389999866485596},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3628000020980835},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.326200008392334},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.30970001220703125},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.2955999970436096},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2840000092983246},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/info16100832","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16100832","pdf_url":"https://www.mdpi.com/2078-2489/16/10/832/pdf?version=1758884256","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"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":"Information","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:391f59d8e78e48e5bcde84bdc2d8a00f","is_oa":true,"landing_page_url":"https://doaj.org/article/391f59d8e78e48e5bcde84bdc2d8a00f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Information, Vol 16, Iss 10, p 832 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/info16100832","is_oa":true,"landing_page_url":"https://doi.org/10.3390/info16100832","pdf_url":"https://www.mdpi.com/2078-2489/16/10/832/pdf?version=1758884256","source":{"id":"https://openalex.org/S4210219776","display_name":"Information","issn_l":"2078-2489","issn":["2078-2489"],"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":"Information","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414556809.pdf","grobid_xml":"https://content.openalex.org/works/W4414556809.grobid-xml"},"referenced_works_count":40,"referenced_works":["https://openalex.org/W2897529137","https://openalex.org/W2949708697","https://openalex.org/W2963125977","https://openalex.org/W2963182550","https://openalex.org/W2968296999","https://openalex.org/W3008105217","https://openalex.org/W3034314779","https://openalex.org/W3035172746","https://openalex.org/W3035346742","https://openalex.org/W3035574168","https://openalex.org/W3113028524","https://openalex.org/W3159695738","https://openalex.org/W3167095230","https://openalex.org/W3205005447","https://openalex.org/W3212492847","https://openalex.org/W4281944033","https://openalex.org/W4310078553","https://openalex.org/W4312410080","https://openalex.org/W4312707458","https://openalex.org/W4312737473","https://openalex.org/W4312934050","https://openalex.org/W4317423407","https://openalex.org/W4382469124","https://openalex.org/W4385731905","https://openalex.org/W4386066365","https://openalex.org/W4386076253","https://openalex.org/W4386076370","https://openalex.org/W4386076430","https://openalex.org/W4390872227","https://openalex.org/W4391047432","https://openalex.org/W4391879019","https://openalex.org/W4393252721","https://openalex.org/W4400447268","https://openalex.org/W4402754159","https://openalex.org/W4404565436","https://openalex.org/W4405489820","https://openalex.org/W4408987436","https://openalex.org/W4409464412","https://openalex.org/W4411472313","https://openalex.org/W4413147024"],"related_works":[],"abstract_inverted_index":{"To":[0],"address":[1],"the":[2,9,53,69,81,117,123,135,139,149,159,162,183,194],"limitation":[3],"of":[4,11,142,197],"receptive":[5,83],"fields":[6],"caused":[7],"by":[8,109,152,169,176],"use":[10],"local":[12,106],"convolutions":[13,66],"in":[14,188],"current":[15],"point":[16,26,54,72,198],"cloud":[17,27,55,73,199],"object":[18,28,190,200],"detection":[19,29,163],"methods,":[20,134],"this":[21],"paper":[22],"proposes":[23],"a":[24,39,45,58,95],"LiDAR":[25],"algorithm":[30],"that":[31],"integrates":[32],"global":[33,76,92],"features.":[34,93],"The":[35,126],"proposed":[36,136],"method":[37,184],"employs":[38],"Voxel":[40,96],"Mapping":[41],"Block":[42,49],"(VMB)":[43],"and":[44,74,85,90,145,155,173,178],"Global":[46],"Feature":[47,98],"Extraction":[48,99],"(GFEB)":[50],"to":[51,67,88,104],"convert":[52],"data":[56],"into":[57],"one-dimensional":[59,124],"long":[60],"sequence.":[61],"It":[62],"then":[63],"utilizes":[64],"non-local":[65],"model":[68],"entire":[70],"voxelized":[71],"incorporate":[75],"contextual":[77],"information,":[78],"thereby":[79],"enhancing":[80,193],"network\u2019s":[82],"field":[84],"its":[86],"capability":[87],"extract":[89],"learn":[91],"Furthermore,":[94],"Channel":[97],"(VCFE)":[100],"module":[101],"is":[102],"designed":[103],"capture":[105],"spatial":[107,118],"information":[108,119],"associating":[110],"features":[111],"across":[112],"different":[113],"channels,":[114],"effectively":[115],"mitigating":[116],"loss":[120],"introduced":[121],"during":[122],"transformation.":[125],"experimental":[127],"results":[128],"demonstrate":[129],"that,":[130],"compared":[131],"with":[132,171],"state-of-the-art":[133],"approach":[137],"improves":[138],"average":[140],"precision":[141],"vehicle,":[143],"pedestrian,":[144],"cyclist":[146],"targets":[147,167],"on":[148],"Waymo":[150],"subset":[151],"0.64%,":[153],"0.71%,":[154],"0.66%,":[156],"respectively.":[157,180],"On":[158],"nuScenes":[160],"dataset,":[161],"accuracy":[164,196],"for":[165],"var":[166],"increased":[168],"0.7%,":[170],"NDS":[172],"mAP":[174],"improving":[175],"0.3%":[177],"0.5%,":[179],"In":[181],"particular,":[182],"exhibits":[185],"outstanding":[186],"performance":[187],"small":[189],"detection,":[191],"significantly":[192],"overall":[195],"detection.":[201]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
