{"id":"https://openalex.org/W4410427423","doi":"https://doi.org/10.1109/tits.2025.3551553","title":"Height3D: A Roadside Visual Framework Based on Height Prediction in Real 3-D Space","display_name":"Height3D: A Roadside Visual Framework Based on Height Prediction in Real 3-D Space","publication_year":2025,"publication_date":"2025-05-16","ids":{"openalex":"https://openalex.org/W4410427423","doi":"https://doi.org/10.1109/tits.2025.3551553"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2025.3551553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3551553","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","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":null,"display_name":"Zhang Zhang","orcid":"https://orcid.org/0009-0000-7253-4018"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhang Zhang","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0000-7253-4018","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087977761","display_name":"Chao Sun","orcid":"https://orcid.org/0000-0002-9324-0892"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Sun","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-9324-0892","affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024806199","display_name":"Bo Wang","orcid":"https://orcid.org/0000-0002-9381-6679"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078005520","display_name":"Bin Guo","orcid":"https://orcid.org/0000-0001-6097-2467"},"institutions":[{"id":"https://openalex.org/I4210113703","display_name":"Henan University of Urban Construction","ror":"https://ror.org/01x1skr92","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210113703"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Guo","raw_affiliation_strings":["Shenzhen Pingshan Urban Construction Investment Company Ltd., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Pingshan Urban Construction Investment Company Ltd., Shenzhen, China","institution_ids":["https://openalex.org/I4210113703"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109297496","display_name":"Da Wen","orcid":"https://orcid.org/0009-0002-4034-5663"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Da Wen","raw_affiliation_strings":["National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101459571","display_name":"Tianyi Zhu","orcid":"https://orcid.org/0000-0002-0811-8930"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyi Zhu","raw_affiliation_strings":["National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":null,"display_name":"Qili Ning","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qili Ning","raw_affiliation_strings":["National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":null,"apc_paid":null,"fwci":1.1332,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.7779823,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"26","issue":"7","first_page":"10909","last_page":"10917"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9966999888420105,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9966999888420105,"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":0.9955999851226807,"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/T10370","display_name":"Traffic and Road Safety","score":0.9836999773979187,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/space","display_name":"Space (punctuation)","score":0.6163891553878784},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5233687162399292},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4402563273906708},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.43469563126564026},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4216260313987732},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.07342451810836792}],"concepts":[{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.6163891553878784},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5233687162399292},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4402563273906708},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.43469563126564026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4216260313987732},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.07342451810836792}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2025.3551553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2025.3551553","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6499999761581421,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3241258132","display_name":null,"funder_award_id":"2023B0909040001","funder_id":"https://openalex.org/F4320329801","funder_display_name":"Shenzhen Research and Development Program"},{"id":"https://openalex.org/G8729846421","display_name":null,"funder_award_id":"KJZD20231023094701003","funder_id":"https://openalex.org/F4320329836","funder_display_name":"Chuzhou Science and Technology Program"}],"funders":[{"id":"https://openalex.org/F4320329801","display_name":"Shenzhen Research and Development Program","ror":null},{"id":"https://openalex.org/F4320329836","display_name":"Chuzhou Science and Technology Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2194775991","https://openalex.org/W2412782625","https://openalex.org/W2565639579","https://openalex.org/W2601564443","https://openalex.org/W2752782242","https://openalex.org/W2897529137","https://openalex.org/W2963840672","https://openalex.org/W2967324759","https://openalex.org/W2968296999","https://openalex.org/W2981857055","https://openalex.org/W3035172746","https://openalex.org/W3035574168","https://openalex.org/W3109395584","https://openalex.org/W3122239467","https://openalex.org/W3171032126","https://openalex.org/W3179888767","https://openalex.org/W3203158837","https://openalex.org/W4224259431","https://openalex.org/W4225793049","https://openalex.org/W4226305814","https://openalex.org/W4312309370","https://openalex.org/W4312443924","https://openalex.org/W4312894406","https://openalex.org/W4312939270","https://openalex.org/W4382464460","https://openalex.org/W4383108631","https://openalex.org/W4386075696","https://openalex.org/W4386076547","https://openalex.org/W4387210688","https://openalex.org/W4389666128","https://openalex.org/W4393153738","https://openalex.org/W4399666337","https://openalex.org/W4399881121","https://openalex.org/W4401414288","https://openalex.org/W4402809322","https://openalex.org/W6784094891","https://openalex.org/W6802311648","https://openalex.org/W6810240388","https://openalex.org/W6811230113","https://openalex.org/W6856809498","https://openalex.org/W6856874339","https://openalex.org/W6857073440"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"vision-based":[3],"roadside":[4,87,129,161],"3D":[5,80,97,113,195],"object":[6,196],"detection":[7,197],"has":[8],"received":[9],"a":[10,86],"great":[11],"deal":[12],"of":[13,20,34,61,76,116,126,181],"attention,":[14],"which":[15,54],"is":[16,55,99,109,137,156,216],"an":[17],"important":[18],"part":[19],"the":[21,28,32,58,79,123,178,201],"Intelligent":[22],"Transportation":[23],"System":[24],"(ITS).":[25],"It":[26],"extends":[27],"perception":[29],"range":[30],"beyond":[31],"limitations":[33],"Autonomous":[35],"Vehicle":[36],"(AV)":[37],"and":[38,63,148,164,191],"enhances":[39,149],"road":[40],"safety.":[41],"While":[42],"previous":[43],"work":[44],"mainly":[45],"focuses":[46],"on":[47,65,92],"height":[48,93,107,124],"prediction":[49,94],"in":[50,78,95,111,117,145,194],"image":[51,118],"2D":[52,119],"space,":[53,98],"limited":[56],"by":[57,83],"perspective":[59],"property":[60],"near-large":[62],"far-small":[64],"images,":[66],"making":[67],"it":[68],"difficult":[69],"for":[70,128,188],"network":[71],"to":[72,121,139,158,170],"understand":[73],"real":[74,96,112],"dimension":[75],"targets":[77,127],"world.":[81],"Inspired":[82],"this":[84],"insight,":[85],"visual":[88],"framework":[89],"Height3D":[90,176],"based":[91],"proposed.":[100],"Height":[101],"Prediction":[102],"Block":[103,135],"(HPB)":[104],"with":[105],"explicit":[106],"supervision":[108],"proposed":[110,154,175,202],"space":[114,120,147],"instead":[115],"predict":[122],"distribution":[125],"view":[130],"transform.":[131],"Also,":[132],"Spatial":[133],"Aware":[134],"(SAB)":[136],"used":[138],"further":[140],"extracts":[141],"spatial":[142],"context":[143],"information":[144],"BEV":[146,151],"fine-grained":[150],"features.":[152],"The":[153,174,214],"method":[155,203],"applied":[157],"two":[159],"large-scale":[160],"benchmarks,":[162],"DAIR-V2X-I":[163],"Rope3D.":[165],"Extensive":[166],"experiments":[167],"are":[168],"performed":[169],"verify":[171],"its":[172],"effectiveness.":[173],"outperforms":[177],"state-of-the-art":[179],"methods":[180],"(1.15,":[182],"7.37,":[183],"4.03)":[184],"Average":[185],"Precision":[186],"(AP)":[187],"Vehicle,":[189],"Pedestrian":[190],"Cyclist":[192],"categories":[193],"task,":[198],"respectively.":[199],"Meanwhile,":[200],"achieves":[204],"31.55":[205],"FPS":[206],"without":[207],"using":[208],"any":[209],"CUDA":[210],"or":[211],"TensorRT":[212],"acceleration.":[213],"code":[215],"available":[217],"at":[218],"https://github.com/zhangzhang2024/Height3D":[219]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}