{"id":"https://openalex.org/W4414216283","doi":"https://doi.org/10.1049/ipr2.70204","title":"SPWS\u2010Transformer: A Study of 3D Target Detection Method Based on Lightweight Depth Prediction With Multi\u2010Scale Fusion","display_name":"SPWS\u2010Transformer: A Study of 3D Target Detection Method Based on Lightweight Depth Prediction With Multi\u2010Scale Fusion","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4414216283","doi":"https://doi.org/10.1049/ipr2.70204"},"language":"en","primary_location":{"id":"doi:10.1049/ipr2.70204","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70204","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70204","source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70204","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005091001","display_name":"Changan Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]},{"id":"https://openalex.org/I4210114785","display_name":"Gansu Provincial Hospital","ror":"https://ror.org/02axars19","country_code":"CN","type":"healthcare","lineage":["https://openalex.org/I4210114785"]},{"id":"https://openalex.org/I4210125346","display_name":"Gansu Institute of Political Science and Law","ror":"https://ror.org/025km4h87","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125346"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang'an Zhang","raw_affiliation_strings":["College of Geomatics Xi'an University of Science and Technology  Xi'an China","Gansu Provincial Map Institute  Lanzhou China"],"affiliations":[{"raw_affiliation_string":"College of Geomatics Xi'an University of Science and Technology  Xi'an China","institution_ids":["https://openalex.org/I110440473"]},{"raw_affiliation_string":"Gansu Provincial Map Institute  Lanzhou China","institution_ids":["https://openalex.org/I4210114785","https://openalex.org/I4210125346"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115589383","display_name":"Yian Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yian Wang","raw_affiliation_strings":["East China Normal University Software Engineering Institute  Shanghai China"],"affiliations":[{"raw_affiliation_string":"East China Normal University Software Engineering Institute  Shanghai China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102757930","display_name":"Ke Xu","orcid":"https://orcid.org/0000-0003-2395-9460"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ke Xu","raw_affiliation_strings":["Faculty of Engineering University of New South Wales  Sydney Australia"],"affiliations":[{"raw_affiliation_string":"Faculty of Engineering University of New South Wales  Sydney Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084513745","display_name":"C. Z. Yuan","orcid":"https://orcid.org/0009-0004-6507-0496"},"institutions":[{"id":"https://openalex.org/I21203515","display_name":"Kazan Federal University","ror":"https://ror.org/05256ym39","country_code":"RU","type":"education","lineage":["https://openalex.org/I21203515"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"ChunHong Yuan","raw_affiliation_strings":["Department of Pre\u2010Engineering Kazan (Volga region) Federal University  Kazan Russia"],"affiliations":[{"raw_affiliation_string":"Department of Pre\u2010Engineering Kazan (Volga region) Federal University  Kazan Russia","institution_ids":["https://openalex.org/I21203515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032970879","display_name":"Fusen Guo","orcid":"https://orcid.org/0009-0007-9142-697X"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Fusen Guo","raw_affiliation_strings":["School of Systems and Computing University of New South Wales  Canberra Australia"],"affiliations":[{"raw_affiliation_string":"School of Systems and Computing University of New South Wales  Canberra Australia","institution_ids":["https://openalex.org/I188329596"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5032970879"],"corresponding_institution_ids":["https://openalex.org/I188329596"],"apc_list":{"value":2000,"currency":"EUR","value_usd":2200},"apc_paid":{"value":2000,"currency":"EUR","value_usd":2200},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.24247372,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9987999796867371,"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":0.9940000176429749,"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/feature-extraction","display_name":"Feature extraction","score":0.6801000237464905},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.650600016117096},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6301000118255615},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5407000184059143},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5030999779701233},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4618000090122223},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3628999888896942}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7645000219345093},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6967999935150146},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6801000237464905},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.650600016117096},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6301000118255615},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5536999702453613},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5407000184059143},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5030999779701233},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4618000090122223},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3628999888896942},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.33230000734329224},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3147999942302704},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.29249998927116394},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.25920000672340393}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1049/ipr2.70204","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70204","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70204","source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1049/ipr2.70204","is_oa":true,"landing_page_url":"https://doi.org/10.1049/ipr2.70204","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1049/ipr2.70204","source":{"id":"https://openalex.org/S83215360","display_name":"IET Image Processing","issn_l":"1751-9659","issn":["1751-9659","1751-9667"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310311714","host_organization_name":"Institution of Engineering and Technology","host_organization_lineage":["https://openalex.org/P4310311714"],"host_organization_lineage_names":["Institution of Engineering and Technology"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IET Image Processing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320965","display_name":"University of New South Wales","ror":"https://ror.org/03r8z3t63"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414216283.pdf","grobid_xml":"https://content.openalex.org/works/W4414216283.grobid-xml"},"referenced_works_count":14,"referenced_works":["https://openalex.org/W2559655401","https://openalex.org/W2623660146","https://openalex.org/W2897529137","https://openalex.org/W2963809933","https://openalex.org/W2997790735","https://openalex.org/W3033696290","https://openalex.org/W3106834807","https://openalex.org/W3114509423","https://openalex.org/W3176319743","https://openalex.org/W4236965008","https://openalex.org/W4237444643","https://openalex.org/W4301409532","https://openalex.org/W4365799809","https://openalex.org/W4376571587"],"related_works":[],"abstract_inverted_index":{"ABSTRACT":[0],"Advanced":[1],"driver":[2],"assistance":[3],"systems":[4],"(ADAS)":[5],"mainly":[6],"consist":[7],"of":[8,22,48,68,122,185,198,233,255,284,308],"three":[9],"components:":[10],"environmental":[11,25],"perception,":[12],"decision":[13],"planning,":[14],"and":[15,36,43,46,54,66,101,116,145,164,215,266],"motion":[16],"control.":[17],"As":[18],"a":[19,74,93,106,189,204,246,261],"fundamental":[20],"component":[21],"the":[23,63,88,127,137,150,160,181,195,225,230,234,275,278,287,298],"ADAS":[24],"perception":[26],"system,":[27],"3D":[28,69,78,235],"object":[29,70,79,236,271],"detection":[30,80,231,237,295],"enables":[31],"vehicles":[32,53],"to":[33,60,86,125,154,193,207,220,240,269],"avoid":[34],"obstacles":[35],"ensure":[37],"driving":[38],"safety":[39],"only":[40],"through":[41],"accurate":[42],"real\u2010time":[44,64,242],"prediction":[45],"localization":[47],"three\u2010dimensional":[49],"targets":[50],"such":[51],"as":[52,169],"pedestrians":[55],"in":[56,294],"road":[57],"scenes.":[58],"Therefore,":[59],"improve":[61,177,241],"both":[62],"performance":[65],"accuracy":[67,296],"detection,":[71],"we":[72,91,111,140,179,244,258],"propose":[73,92],"lightweight":[75],"depth":[76,102,156,165,199,212,265],"prediction\u2010based":[77],"model":[81,303],"with":[82,249,290],"multi\u2010scale":[83,98,107,114],"fusion\u2014SPWS\u2010Transformer.":[84],"First,":[85],"enhance":[87,126,270],"model's":[89],"accuracy,":[90,178],"feature":[94,99,108,120,129,138,152,157,162,166,190,200,213],"extraction":[95,130],"network":[96,173],"incorporating":[97],"fusion":[100,109],"prediction.":[103],"By":[104,252],"designing":[105,188],"module,":[110],"effectively":[112],"combine":[113],"semantic":[115],"fine\u2010grained":[117],"information":[118,135],"from":[119,136],"maps":[121,153,163,167,214],"different":[123,256],"scales":[124],"network's":[128],"capability.":[131],"To":[132,175],"capture":[133,221],"spatial":[134],"maps,":[139],"apply":[141],"convolution,":[142],"group":[143],"normalization,":[144],"nonlinear":[146],"activation":[147],"operations":[148],"on":[149,211,274],"fused":[151,161],"generate":[155],"maps.":[158,201],"Both":[159],"serve":[168],"inputs":[170],"for":[171,286],"subsequent":[172],"stages.":[174],"further":[176],"leverage":[180],"long\u2010range":[182],"modelling":[183],"advantages":[184],"Transformers":[186],"by":[187],"enhancement":[191],"encoder":[192,206],"strengthen":[194],"representation":[196],"capability":[197,232],"We":[202],"incorporate":[203],"dilated":[205],"perform":[208],"positional":[209],"encoding":[210],"utilize":[216],"multi\u2010head":[217],"self\u2010attention":[218],"mechanisms":[219],"contextual":[222],"relationships":[223],"within":[224],"input":[226],"scene,":[227],"thereby":[228],"enhancing":[229],"network.":[238],"Then,":[239],"performance,":[243],"design":[245],"decoder":[247],"structure":[248],"scale\u2010aware":[250,262],"attention.":[251],"predefining":[253],"masks":[254],"scales,":[257],"adaptively":[259],"learn":[260],"filter":[263],"using":[264],"visual":[267],"features":[268],"queries.":[272],"Finally,":[273],"KITTI":[276],"dataset,":[277],"improved":[279],"algorithm":[280],"achieves":[281,304],"an":[282,305],"AP":[283],"24.66%":[285],"car":[288],"category,":[289],"more":[291],"significant":[292],"improvements":[293],"under":[297],"\u2018hard\u2019":[299],"difficulty":[300],"level.":[301],"The":[302],"inference":[306],"time":[307],"24":[309],"ms.":[310]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}