{"id":"https://openalex.org/W3207105331","doi":"https://doi.org/10.1109/icra48506.2021.9561245","title":"FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection","display_name":"FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection","publication_year":2021,"publication_date":"2021-05-30","ids":{"openalex":"https://openalex.org/W3207105331","doi":"https://doi.org/10.1109/icra48506.2021.9561245","mag":"3207105331"},"language":"en","primary_location":{"id":"doi:10.1109/icra48506.2021.9561245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5100339158","display_name":"Yi Wei","orcid":"https://orcid.org/0000-0002-9886-6851"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yi Wei","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035410669","display_name":"Shang Su","orcid":"https://orcid.org/0000-0003-0228-5380"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shang Su","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100460385","display_name":"Jiwen Lu","orcid":"https://orcid.org/0000-0002-6121-5529"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiwen Lu","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100620306","display_name":"Jie Zhou","orcid":"https://orcid.org/0000-0001-7701-234X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Zhou","raw_affiliation_strings":["Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]},{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105","https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100339158"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":2.5248,"has_fulltext":false,"cited_by_count":35,"citation_normalized_percentile":{"value":0.91288754,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4348","last_page":"4354"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9993000030517578,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.996999979019165,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.8035691976547241},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.7905541658401489},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7731419205665588},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6940733194351196},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6754934787750244},{"id":"https://openalex.org/keywords/frustum","display_name":"Frustum","score":0.6646651029586792},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6537551879882812},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.539039134979248},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5315465927124023},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5163289308547974},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5153269171714783},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.507904589176178},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4724564850330353},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4163277745246887},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36262065172195435},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19494444131851196},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12295448780059814},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08090493083000183}],"concepts":[{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.8035691976547241},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.7905541658401489},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7731419205665588},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6940733194351196},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6754934787750244},{"id":"https://openalex.org/C97402662","wikidata":"https://www.wikidata.org/wiki/Q846235","display_name":"Frustum","level":2,"score":0.6646651029586792},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6537551879882812},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.539039134979248},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5315465927124023},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5163289308547974},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5153269171714783},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.507904589176178},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4724564850330353},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4163277745246887},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36262065172195435},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19494444131851196},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12295448780059814},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08090493083000183},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra48506.2021.9561245","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra48506.2021.9561245","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1023919524","display_name":null,"funder_award_id":", Grant","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1231421488","display_name":null,"funder_award_id":"under","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G340251319","display_name":null,"funder_award_id":"61822603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G391238517","display_name":null,"funder_award_id":", and","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4397514795","display_name":null,"funder_award_id":"U1813218","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6372554807","display_name":null,"funder_award_id":"U1713214","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322392","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":70,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1686810756","https://openalex.org/W1861492603","https://openalex.org/W1923184257","https://openalex.org/W2085261163","https://openalex.org/W2096579040","https://openalex.org/W2108598243","https://openalex.org/W2150066425","https://openalex.org/W2555182955","https://openalex.org/W2555618208","https://openalex.org/W2560544142","https://openalex.org/W2560609797","https://openalex.org/W2594519801","https://openalex.org/W2613718673","https://openalex.org/W2799404913","https://openalex.org/W2897529137","https://openalex.org/W2919534447","https://openalex.org/W2949708697","https://openalex.org/W2951517617","https://openalex.org/W2954174912","https://openalex.org/W2962807143","https://openalex.org/W2962835968","https://openalex.org/W2963121255","https://openalex.org/W2963150697","https://openalex.org/W2963400571","https://openalex.org/W2963446712","https://openalex.org/W2963794551","https://openalex.org/W2964062501","https://openalex.org/W2964166085","https://openalex.org/W2968296999","https://openalex.org/W2969050719","https://openalex.org/W2969322483","https://openalex.org/W2981581281","https://openalex.org/W2981857055","https://openalex.org/W2981949127","https://openalex.org/W2982363097","https://openalex.org/W2988715931","https://openalex.org/W2997188997","https://openalex.org/W2999947750","https://openalex.org/W3003618643","https://openalex.org/W3004148335","https://openalex.org/W3004237909","https://openalex.org/W3004287531","https://openalex.org/W3004414032","https://openalex.org/W3005819241","https://openalex.org/W3008105217","https://openalex.org/W3008681115","https://openalex.org/W3010454265","https://openalex.org/W3034314779","https://openalex.org/W3034602892","https://openalex.org/W3035057392","https://openalex.org/W3035346742","https://openalex.org/W3089401811","https://openalex.org/W3090896893","https://openalex.org/W3092761163","https://openalex.org/W3106250896","https://openalex.org/W3108381027","https://openalex.org/W3113876851","https://openalex.org/W6620707391","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6730003152","https://openalex.org/W6735463952","https://openalex.org/W6739778489","https://openalex.org/W6763422710","https://openalex.org/W6764117818","https://openalex.org/W6772595511","https://openalex.org/W6776283018","https://openalex.org/W6780776872","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2540960825","https://openalex.org/W2613186388","https://openalex.org/W2187221949","https://openalex.org/W3211653591","https://openalex.org/W2766547489","https://openalex.org/W4313854567","https://openalex.org/W2734888972","https://openalex.org/W2536634271","https://openalex.org/W2739874619","https://openalex.org/W2997790735"],"abstract_inverted_index":{"In":[0],"this":[1,45],"paper,":[2],"we":[3,47,103],"investigate":[4],"the":[5,80,114,146],"problem":[6],"of":[7,23,68,133],"weakly":[8],"supervised":[9,143],"3D":[10,16,26,41,63,72,75,110,118,130,135,161],"vehicle":[11],"detection.":[12],"Conventional":[13],"methods":[14,144],"for":[15,40],"object":[17],"detection":[18],"usually":[19],"require":[20],"vast":[21],"amounts":[22],"manually":[24],"labelled":[25],"data":[27],"as":[28],"supervision":[29],"signals.":[30],"However,":[31],"annotating":[32],"large":[33],"datasets":[34],"needs":[35],"huge":[36],"human":[37],"efforts,":[38],"especially":[39],"area.":[42],"To":[43],"tackle":[44],"problem,":[46],"propose":[48],"a":[49,83,129],"frustum-aware":[50],"geometric":[51],"reasoning":[52],"(FGR)":[53],"method":[54,66,124],"to":[55,91,108,127,156],"detect":[56,158],"vehicles":[57],"in":[58,113,160],"point":[59,170],"clouds":[60],"without":[61],"any":[62,134],"annotations.":[64],"Our":[65],"consists":[67],"two":[69],"stages:":[70],"coarse":[71],"segmentation":[73,101],"and":[74,168],"bounding":[76,97,111,166],"box":[77],"estimation.":[78],"For":[79],"first":[81],"stage,":[82],"context-aware":[84],"adaptive":[85],"region":[86],"growing":[87],"algorithm":[88],"is":[89,154],"designed":[90],"segment":[92],"objects":[93,159],"based":[94],"on":[95,145],"2D":[96,165],"boxes.":[98],"Leveraging":[99],"predicted":[100],"masks,":[102],"develop":[104],"an":[105],"anti-noise":[106],"approach":[107],"estimate":[109],"boxes":[112,167],"second":[115],"stage.":[116],"Finally":[117],"pseudo":[119],"labels":[120],"generated":[121],"by":[122],"our":[123],"are":[125],"utilized":[126],"train":[128],"detector.":[131],"Independent":[132],"groundtruth,":[136],"FGR":[137],"reaches":[138],"comparable":[139],"performance":[140],"with":[141,163],"fully":[142],"KITTI":[147],"dataset.":[148],"The":[149],"findings":[150],"indicate":[151],"that":[152],"it":[153],"able":[155],"accurately":[157],"space":[162],"only":[164],"sparse":[169],"clouds.":[171]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}