{"id":"https://openalex.org/W7207566254","doi":"https://doi.org/10.1117/12.3120297","title":"Estimation of range-gated depth in autonomous driving with RGB geometric priors","display_name":"Estimation of range-gated depth in autonomous driving with RGB geometric priors","publication_year":2026,"publication_date":"2026-09-03","ids":{"openalex":"https://openalex.org/W7207566254","doi":"https://doi.org/10.1117/12.3120297"},"language":"en","primary_location":{"id":"doi:10.1117/12.3120297","doi":"https://doi.org/10.1117/12.3120297","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.3120297","pdf_url":null,"source":{"id":"https://openalex.org/S7407107304","display_name":"AI Photonics Technology Symposium (APTS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Photonics Technology Symposium (APTS 2026)","raw_type":"proceedings-article"},"volume":null,"type":"conference-abstract","is_traditional":false,"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/A5149967919","display_name":"Hao Chen","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Chen","raw_affiliation_strings":["Space Engineering University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University (China)","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030813571","display_name":"Chenglong Luan","orcid":"https://orcid.org/0000-0002-7034-0102","observed_orcids":["https://orcid.org/0000-0002-7034-0102"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenglong Luan","raw_affiliation_strings":["Space Engineering University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University (China)","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077425135","display_name":"Huichao Guo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huichao Guo","raw_affiliation_strings":["Space Engineering University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University (China)","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084163246","display_name":"Haijing Zheng","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haijing Zheng","raw_affiliation_strings":["Space Engineering University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University (China)","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5140780570","display_name":"Rong Li","orcid":"https://orcid.org/0009-0009-3090-205X","observed_orcids":["https://orcid.org/0009-0009-3090-205X"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Li","raw_affiliation_strings":["Space Engineering University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University (China)","institution_ids":["https://openalex.org/I4210148107"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5122637176","display_name":"Laixian Zhang","orcid":"https://orcid.org/0009-0004-6437-1289","observed_orcids":["https://orcid.org/0009-0004-6437-1289"]},"institutions":[{"id":"https://openalex.org/I4210148107","display_name":"Space Engineering University","ror":"https://ror.org/04rj1td02","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210148107"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Laixian Zhang","raw_affiliation_strings":["Space Engineering University (China)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Space Engineering University (China)","institution_ids":["https://openalex.org/I4210148107"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210148107"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3","last_page":"3"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.5023999810218811,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.5023999810218811,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.46560001373291016,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.00989999994635582,"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/range-gated-imaging","display_name":"range-gated imaging","score":0.8840000033378601},{"id":"https://openalex.org/keywords/depth-estimation","display_name":"depth estimation","score":0.9380000233650208},{"id":"https://openalex.org/keywords/autonomous-driving-perception","display_name":"autonomous driving perception","score":0.8610000014305115},{"id":"https://openalex.org/keywords/cross-modal-fusion","display_name":"cross-modal fusion","score":0.7649999856948853},{"id":"https://openalex.org/keywords/cross-attention","display_name":"cross-attention","score":0.902999997138977},{"id":"https://openalex.org/keywords/encoder-decoder-transformer","display_name":"transformer encoder-decoder","score":0.7059999704360962},{"id":"https://openalex.org/keywords/edge-alignment","display_name":"edge alignment","score":0.7649999856948853}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.82669997215271},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7343999743461609},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6819999814033508},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.599399983882904},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.5699999928474426},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4081000089645386},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.3815999925136566},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.3677999973297119},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.3662000000476837},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.337799996137619},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.3212999999523163},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3059999942779541},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.287200003862381},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2831000089645386},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.2721000015735626},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2583000063896179},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.257999986410141},{"id":"https://openalex.org/C50045419","wikidata":"https://www.wikidata.org/wiki/Q7575328","display_name":"Specular highlight","level":3,"score":0.257099986076355},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.25609999895095825},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.25600001215934753},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.2547999918460846},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.3120297","doi":"https://doi.org/10.1117/12.3120297","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.3120297","pdf_url":null,"source":{"id":"https://openalex.org/S7407107304","display_name":"AI Photonics Technology Symposium (APTS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"AI Photonics Technology Symposium (APTS 2026)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4415042872","https://openalex.org/W7124914107","https://openalex.org/W3157614523","https://openalex.org/W4226055020","https://openalex.org/W4410704558","https://openalex.org/W4303650407","https://openalex.org/W2991840778","https://openalex.org/W3011724875","https://openalex.org/W3205067660","https://openalex.org/W7154456997"],"abstract_inverted_index":{"Existing":[0],"deep":[1],"learning-based":[2],"3D":[3,228],"range-gated":[4,55,227],"imaging":[5,229],"methods,":[6],"like":[7],"Gated2Depth,":[8],"still":[9],"lack":[10],"the":[11,68,91,122,152,164,171,173,212],"ability":[12,125],"to":[13,21,76,105,150],"fully":[14],"exploit":[15],"color":[16],"cues,":[17],"have":[18],"high":[19],"sensitivity":[20],"specular":[22],"noise,":[23],"and":[24,65,86,115,135,142,157,180,210,214],"produces":[25],"undesirable":[26],"local":[27,137],"artifacts":[28],"in":[29,184,207,230],"autonomous":[30,231],"driving":[31],"situations.":[32],"To":[33],"overcome":[34],"these":[35],"limitations,":[36],"we":[37],"suggest":[38],"RGD-Net,":[39],"a":[40,97,102],"new":[41],"depth":[42,108,144,155,198],"estimation":[43],"network":[44,51],"that":[45,168,222],"incorporates":[46],"RGB":[47,61,119],"geometric":[48,78,159],"priors.":[49],"The":[50,195],"employs":[52,96],"three":[53],"consecutive":[54],"frames":[56],"as":[57,81],"its":[58],"input.":[59],"Synchronized":[60],"images":[62,112],"are":[63,147],"projected":[64],"aligned":[66],"with":[67,101,113,170],"gated":[69,111],"coordinate":[70],"system":[71],"using":[72],"camera":[73],"calibration":[74],"parameters":[75],"provide":[77],"priors":[79],"such":[80],"scene":[82,158],"edges,":[83],"texture":[84,116],"gradients,":[85],"spatial":[87,133],"structures.":[88,160],"Based":[89],"on":[90,163],"encoder-Transformer-decoder":[92],"architecture,":[93],"this":[94],"framework":[95],"cross-modal":[98],"fusion":[99],"strategy":[100],"cross-attention":[103],"mechanism":[104],"effectively":[106,203],"combine":[107],"features":[109],"from":[110,118],"edge":[114],"information":[117],"images.":[120],"Using":[121],"global":[123],"modeling":[124],"of":[126,154,216],"Transformer,":[127],"our":[128],"model":[129],"can":[130],"capture":[131],"long-range":[132],"dependencies":[134],"reduce":[136],"noise":[138],"interference.":[139],"Edge":[140],"alignment":[141],"relative":[143],"consistency":[145],"constraints":[146],"further":[148],"designed":[149],"facilitate":[151],"learning":[153],"boundaries":[156],"Experimental":[161,219],"results":[162,220],"Gated2Depth":[165],"dataset":[166],"demonstrate":[167],"compared":[169],"baseline,":[172],"proposed":[174],"method":[175],"reduces":[176],"MAE":[177],"by":[178,182,191],"42.84%":[179],"RMSE":[181],"29.00%":[183],"daytime":[185],"scenarios,":[186],"while":[187],"boosting":[188],"\u03b41":[189],"accuracy":[190,215],"18.89":[192],"percentage":[193],"points.":[194],"generated":[196],"dense":[197],"maps":[199],"exhibit":[200],"clearer":[201],"boundaries,":[202],"correcting":[204],"erroneous":[205],"predictions":[206],"depth-discontinuous":[208],"regions":[209],"improving":[211],"integrity":[213],"object":[217],"contours.":[218],"indicate":[221],"RGD-Net":[223],"is":[224],"promising":[225],"for":[226],"perception":[232],"tasks.":[233]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-09-04T00:00:00"}
