{"id":"https://openalex.org/W4383066376","doi":"https://doi.org/10.1109/icra48891.2023.10160433","title":"Joint Semi-Supervised and Active Learning via 3D Consistency for 3D Object Detection","display_name":"Joint Semi-Supervised and Active Learning via 3D Consistency for 3D Object Detection","publication_year":2023,"publication_date":"2023-05-29","ids":{"openalex":"https://openalex.org/W4383066376","doi":"https://doi.org/10.1109/icra48891.2023.10160433"},"language":"en","primary_location":{"id":"doi:10.1109/icra48891.2023.10160433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","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/A5102531112","display_name":"Sihwan Hwang","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sihwan Hwang","raw_affiliation_strings":["Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032573421","display_name":"Sanmin Kim","orcid":"https://orcid.org/0000-0002-4042-6570"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sanmin Kim","raw_affiliation_strings":["Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100600320","display_name":"Young-Seok Kim","orcid":"https://orcid.org/0000-0002-9400-2204"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngseok Kim","raw_affiliation_strings":["Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091555350","display_name":"Dongsuk Kum","orcid":"https://orcid.org/0000-0002-2590-4845"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongsuk Kum","raw_affiliation_strings":["Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cho Chun Shik Graduate School of Mobility, KAIST,Daejeon,Republic of Korea,34051","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.3333,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57340662,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4819","last_page":"4825"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9994000196456909,"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":0.9994000196456909,"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":0.9994000196456909,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.8015488386154175},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.7902162075042725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7200573086738586},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.70099937915802},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6618456244468689},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6386213302612305},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6267341375350952},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5918653607368469},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5906625390052795},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5799071788787842},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5790987014770508},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5342860221862793},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5215856432914734},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.48823097348213196},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.474817156791687},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.42904993891716003},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.41478702425956726},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.29526960849761963},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14195170998573303},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08066174387931824}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8015488386154175},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.7902162075042725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7200573086738586},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.70099937915802},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6618456244468689},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6386213302612305},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6267341375350952},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5918653607368469},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5906625390052795},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5799071788787842},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5790987014770508},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5342860221862793},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5215856432914734},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.48823097348213196},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.474817156791687},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.42904993891716003},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.41478702425956726},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29526960849761963},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14195170998573303},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08066174387931824},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48891.2023.10160433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48891.2023.10160433","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6860577065","display_name":null,"funder_award_id":"2021-0-00951,2022R1A2C200494412","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W582134693","https://openalex.org/W1579853615","https://openalex.org/W1861492603","https://openalex.org/W1872312298","https://openalex.org/W1959608418","https://openalex.org/W2031489346","https://openalex.org/W2127816222","https://openalex.org/W2141100699","https://openalex.org/W2150066425","https://openalex.org/W2184393491","https://openalex.org/W2593021375","https://openalex.org/W2774918944","https://openalex.org/W2783822844","https://openalex.org/W2798820905","https://openalex.org/W2893733848","https://openalex.org/W2897529137","https://openalex.org/W2950776302","https://openalex.org/W2951061410","https://openalex.org/W2951786554","https://openalex.org/W2953070460","https://openalex.org/W2956371155","https://openalex.org/W2964167449","https://openalex.org/W2970369250","https://openalex.org/W2970624554","https://openalex.org/W2978725006","https://openalex.org/W2984303785","https://openalex.org/W2986514296","https://openalex.org/W3035057392","https://openalex.org/W3035574168","https://openalex.org/W3095809828","https://openalex.org/W3096831136","https://openalex.org/W3110608319","https://openalex.org/W3118457089","https://openalex.org/W3120338137","https://openalex.org/W3166089996","https://openalex.org/W3167095230","https://openalex.org/W3184557372","https://openalex.org/W3187627504","https://openalex.org/W3217804345","https://openalex.org/W4230649179","https://openalex.org/W4287236013","https://openalex.org/W4287692693","https://openalex.org/W4295521015","https://openalex.org/W6617145748","https://openalex.org/W6639102338","https://openalex.org/W6639393196","https://openalex.org/W6640963894","https://openalex.org/W6678881507","https://openalex.org/W6686211706","https://openalex.org/W6687506355","https://openalex.org/W6729482032","https://openalex.org/W6733814495","https://openalex.org/W6734269522","https://openalex.org/W6735374517","https://openalex.org/W6747231328","https://openalex.org/W6754665663","https://openalex.org/W6755088026","https://openalex.org/W6761687610","https://openalex.org/W6764588566","https://openalex.org/W6766773940","https://openalex.org/W6781216420","https://openalex.org/W6792663124"],"related_works":["https://openalex.org/W3036286480","https://openalex.org/W3192357901","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W4390524233"],"abstract_inverted_index":{"Autonomous":[0],"driving":[1,13],"powered":[2],"by":[3,187],"deep":[4],"learning":[5,34,74,107,165],"requires":[6],"large-scale,":[7],"high-quality":[8],"training":[9,150],"data":[10,24,44,87],"from":[11],"diverse":[12],"environments":[14],"to":[15,39,125,178],"operate":[16],"effectively":[17],"worldwide.":[18],"However,":[19],"collecting":[20],"and":[21,27,56,88,105,140,173],"annotating":[22],"such":[23],"is":[25],"costly":[26],"time-consuming.":[28],"To":[29],"address":[30],"this":[31,67],"challenge,":[32],"active":[33,73,106,164],"methods":[35,51],"have":[36],"been":[37],"explored":[38],"select":[40],"the":[41,61,83,95,111,157,175,185],"most":[42,49],"informative":[43],"samples":[45],"for":[46,76,145],"training.":[47],"Nevertheless,":[48],"existing":[50],"focus":[52],"on":[53,156],"2D":[54],"tasks":[55,80],"do":[57],"not":[58],"fully":[59],"exploit":[60],"value":[62],"of":[63,85,98,113],"unlabeled":[64],"data.":[65],"In":[66],"paper,":[68],"we":[69],"propose":[70],"a":[71],"semi-supervised":[72,104,149,163],"approach":[75,166,183],"3D":[77,96,116],"object":[78,117],"detection":[79,118],"that":[81,134,161],"leverages":[82],"potential":[84],"collected":[86],"reduces":[89],"annotation":[90,146],"costs.":[91],"Our":[92,120,182],"method":[93],"considers":[94],"consistency":[97],"bounding":[99,127],"box":[100,128],"predictions":[101],"in":[102],"both":[103],"processes,":[108],"thereby":[109],"improving":[110],"performance":[112],"point":[114],"cloud-based":[115],"models.":[119],"framework":[121],"specifically":[122],"utilizes":[123],"self-supervision":[124],"decrease":[126],"uncertainties.":[129],"Moreover,":[130],"it":[131],"selects":[132,167],"objects":[133,168],"are":[135],"either":[136],"occluded":[137,180],"or":[138],"distant":[139],"still":[141],"exhibit":[142],"high":[143,170],"uncertainty":[144],"even":[147],"after":[148],"has":[151],"decreased":[152],"their":[153],"uncertainty.":[154],"Experiments":[155],"KITTI":[158],"dataset":[159],"demonstrate":[160],"our":[162],"with":[169],"measurement":[171],"uncertainties":[172],"enhances":[174],"model's":[176],"ability":[177],"detect":[179],"objects.":[181],"improves":[184],"baseline":[186],"more":[188],"than":[189],"60%":[190],"(+17.12":[191],"mAP)":[192],"when":[193],"using":[194],"only":[195],"1500":[196],"annotated":[197],"frames.":[198]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}