{"id":"https://openalex.org/W4386450043","doi":"https://doi.org/10.1109/iccc57788.2023.10233322","title":"An Efficient Multimodal Fusion Pipeline for Nighttime 3D Object Detection with PointrendPainting","display_name":"An Efficient Multimodal Fusion Pipeline for Nighttime 3D Object Detection with PointrendPainting","publication_year":2023,"publication_date":"2023-08-10","ids":{"openalex":"https://openalex.org/W4386450043","doi":"https://doi.org/10.1109/iccc57788.2023.10233322"},"language":"en","primary_location":{"id":"doi:10.1109/iccc57788.2023.10233322","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccc57788.2023.10233322","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","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/A5049365615","display_name":"Xiting Peng","orcid":"https://orcid.org/0000-0002-3230-0329"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiting Peng","raw_affiliation_strings":["Shenyang University of Technology,School of Information Science and Engineering,Shenyang,China,110178"],"affiliations":[{"raw_affiliation_string":"Shenyang University of Technology,School of Information Science and Engineering,Shenyang,China,110178","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043108214","display_name":"T Zhang","orcid":"https://orcid.org/0000-0002-7251-7282"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingkai Zhang","raw_affiliation_strings":["Shenyang University of Technology,School of Information Science and Engineering,Shenyang,China,110178"],"affiliations":[{"raw_affiliation_string":"Shenyang University of Technology,School of Information Science and Engineering,Shenyang,China,110178","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419434","display_name":"Xiaoyu Zhang","orcid":"https://orcid.org/0000-0003-1630-6058"},"institutions":[{"id":"https://openalex.org/I157507598","display_name":"Shenyang University of Technology","ror":"https://ror.org/00d7f8730","country_code":"CN","type":"education","lineage":["https://openalex.org/I157507598"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Zhang","raw_affiliation_strings":["Shenyang University of Technology,School of Artificial Intelligence,Shenyang,China,110178"],"affiliations":[{"raw_affiliation_string":"Shenyang University of Technology,School of Artificial Intelligence,Shenyang,China,110178","institution_ids":["https://openalex.org/I157507598"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061453937","display_name":"Mianxiong Dong","orcid":"https://orcid.org/0000-0002-2788-3451"},"institutions":[{"id":"https://openalex.org/I41725924","display_name":"Muroran Institute of Technology","ror":"https://ror.org/04rymkk69","country_code":"JP","type":"education","lineage":["https://openalex.org/I41725924"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Mianxiong Dong","raw_affiliation_strings":["Muroran Institute of Technology,Department of Sciences and Informatics,Muroran,Japan,050-8585"],"affiliations":[{"raw_affiliation_string":"Muroran Institute of Technology,Department of Sciences and Informatics,Muroran,Japan,050-8585","institution_ids":["https://openalex.org/I41725924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106707877","display_name":"Kaoru Ota","orcid":"https://orcid.org/0000-0002-3382-1652"},"institutions":[{"id":"https://openalex.org/I41725924","display_name":"Muroran Institute of Technology","ror":"https://ror.org/04rymkk69","country_code":"JP","type":"education","lineage":["https://openalex.org/I41725924"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kaoru Ota","raw_affiliation_strings":["Muroran Institute of Technology,Department of Sciences and Informatics,Muroran,Japan,050-8585"],"affiliations":[{"raw_affiliation_string":"Muroran Institute of Technology,Department of Sciences and Informatics,Muroran,Japan,050-8585","institution_ids":["https://openalex.org/I41725924"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5049365615"],"corresponding_institution_ids":["https://openalex.org/I157507598"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10377371,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"130","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9937000274658203,"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/computer-science","display_name":"Computer science","score":0.8011974096298218},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.74162358045578},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.7145484685897827},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.712515115737915},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6506550312042236},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6289145350456238},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5707619786262512},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.45223870873451233},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.43803030252456665},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.4239233136177063},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.36051809787750244},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.17888328433036804}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8011974096298218},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.74162358045578},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7145484685897827},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.712515115737915},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6506550312042236},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6289145350456238},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5707619786262512},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.45223870873451233},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.43803030252456665},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.4239233136177063},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36051809787750244},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.17888328433036804},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccc57788.2023.10233322","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccc57788.2023.10233322","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE/CIC International Conference on Communications in China (ICCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.7799999713897705}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321408","display_name":"Ministry of Education","ror":"https://ror.org/01p262204"},{"id":"https://openalex.org/F4320323086","display_name":"Natural Science Foundation of Liaoning Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2468368736","https://openalex.org/W2555618208","https://openalex.org/W2897529137","https://openalex.org/W2902285895","https://openalex.org/W2949708697","https://openalex.org/W2954174912","https://openalex.org/W2964062501","https://openalex.org/W2968296999","https://openalex.org/W2996010494","https://openalex.org/W3035358681","https://openalex.org/W3035461736","https://openalex.org/W3101584909","https://openalex.org/W3117804044","https://openalex.org/W3126988251","https://openalex.org/W3176287975","https://openalex.org/W6745673378","https://openalex.org/W6754918364","https://openalex.org/W6756892258"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W4281783339","https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W3109712509"],"abstract_inverted_index":{"Accurate":[0],"detection":[1,108,162],"of":[2,19,30,39,43,53,97,109,118],"objects":[3],"in":[4,41,46,55,82],"the":[5,17,20,23,51,83,91,107,116,136,139],"three-dimensional":[6],"world":[7,26],"is":[8],"a":[9,37],"core":[10],"problem":[11,117],"for":[12],"autonomous":[13,56],"vehicles":[14],"and":[15,32,36,78,99,151],"ensures":[16],"safety":[18],"vehicles.":[21,57],"Nevertheless,":[22],"complex":[24],"real":[25],"has":[27],"different":[28],"degrees":[29],"occlusion":[31],"night":[33,119],"driving":[34,120],"conditions,":[35],"lack":[38],"detail":[40],"images":[42],"road":[44,132],"scenes":[45],"low-light":[47],"conditions":[48],"may":[49],"increase":[50],"risk":[52],"collisions":[54],"And":[58,158],"many":[59],"previous":[60,149],"unimodal":[61],"methods":[62],"do":[63],"not":[64],"solve":[65,115],"such":[66],"problems":[67],"well.":[68],"In":[69,112],"this":[70],"paper,":[71],"we":[72,122],"propose":[73],"PointrendPainting,":[74],"which":[75],"fuses":[76,100],"image":[77],"point":[79,102],"cloud":[80],"data":[81,85],"early":[84],"processing":[86],"stage.":[87],"The":[88],"method":[89,144],"exploits":[90],"efficient":[92],"object":[93],"boundary":[94],"segmentation":[95],"effect":[96],"Pointrend":[98],"LiDAR":[101],"clouds":[103],"to":[104,114,129,165],"effectively":[105],"improve":[106],"occluded":[110],"objects.":[111],"addition,":[113],"safety,":[121],"leverage":[123],"Cycle-Consistent":[124],"Generative":[125],"Adversarial":[126],"Networks":[127],"(CycleGAN)":[128],"generate":[130],"nighttime":[131,141,156],"images.":[133],"Then":[134],"train":[135],"model":[137],"on":[138],"new":[140],"KITTI.":[142],"Our":[143],"generally":[145],"improves":[146],"2%-3%":[147],"over":[148],"work":[150],"can":[152],"run":[153],"well":[154],"under":[155],"conditions.":[157],"simple":[159],"car":[160],"class":[161],"accuracy":[163],"up":[164],"91.77%.":[166]},"counts_by_year":[],"updated_date":"2025-12-21T01:58:51.020947","created_date":"2025-10-10T00:00:00"}