{"id":"https://openalex.org/W4285117287","doi":"https://doi.org/10.1109/tits.2022.3170870","title":"Semantic Guided Long Range Stereo Depth Estimation for Safer Autonomous Vehicle Applications","display_name":"Semantic Guided Long Range Stereo Depth Estimation for Safer Autonomous Vehicle Applications","publication_year":2022,"publication_date":"2022-05-09","ids":{"openalex":"https://openalex.org/W4285117287","doi":"https://doi.org/10.1109/tits.2022.3170870"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3170870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3170870","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":"https://openalex.org/A5060353361","display_name":"WeiQin Chuah","orcid":"https://orcid.org/0000-0001-6020-4660"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Weiqin Chuah","raw_affiliation_strings":["School of Engineering, RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-6020-4660","affiliations":[{"raw_affiliation_string":"School of Engineering, RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022576557","display_name":"Ruwan Tennakoon","orcid":"https://orcid.org/0000-0001-8909-5728"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ruwan Tennakoon","raw_affiliation_strings":["School of Science, RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-8909-5728","affiliations":[{"raw_affiliation_string":"School of Science, RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050176259","display_name":"Reza Hoseinnezhad","orcid":"https://orcid.org/0000-0001-9525-1467"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Reza Hoseinnezhad","raw_affiliation_strings":["School of Engineering, RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9525-1467","affiliations":[{"raw_affiliation_string":"School of Engineering, RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031492664","display_name":"David Suter","orcid":"https://orcid.org/0000-0001-6306-3023"},"institutions":[{"id":"https://openalex.org/I12079687","display_name":"Edith Cowan University","ror":"https://ror.org/05jhnwe22","country_code":"AU","type":"education","lineage":["https://openalex.org/I12079687"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"David Suter","raw_affiliation_strings":["School of Science, Edith Cowan University, Joondalup, WA, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Science, Edith Cowan University, Joondalup, WA, Australia","institution_ids":["https://openalex.org/I12079687"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067249512","display_name":"Alireza Bab\u2010Hadiashar","orcid":"https://orcid.org/0000-0002-6192-2303"},"institutions":[{"id":"https://openalex.org/I82951845","display_name":"RMIT University","ror":"https://ror.org/04ttjf776","country_code":"AU","type":"education","lineage":["https://openalex.org/I82951845"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Alireza Bab-Hadiashar","raw_affiliation_strings":["School of Engineering, RMIT University, Melbourne, VIC, Australia"],"raw_orcid":"https://orcid.org/0000-0002-6192-2303","affiliations":[{"raw_affiliation_string":"School of Engineering, RMIT University, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I82951845"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2512,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.89367161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"23","issue":"10","first_page":"18916","last_page":"18926"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":1.0,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9987000226974487,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7308445572853088},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6794086694717407},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6358140110969543},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.561579704284668},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5284478664398193},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5158593058586121},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5137399435043335},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4755396842956543},{"id":"https://openalex.org/keywords/depth-perception","display_name":"Depth perception","score":0.4537402391433716},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.4276081919670105},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.29735156893730164},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.15917235612869263},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.12432348728179932}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7308445572853088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6794086694717407},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6358140110969543},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.561579704284668},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5284478664398193},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5158593058586121},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5137399435043335},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4755396842956543},{"id":"https://openalex.org/C52672216","wikidata":"https://www.wikidata.org/wiki/Q1749840","display_name":"Depth perception","level":3,"score":0.4537402391433716},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.4276081919670105},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.29735156893730164},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.15917235612869263},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.12432348728179932},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tits.2022.3170870","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3170870","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"},{"id":"pmh:oai:ro.ecu.edu.au:ecuworks2022-2026-1885","is_oa":false,"landing_page_url":"https://ro.ecu.edu.au/ecuworks2022-2026/885","pdf_url":null,"source":{"id":"https://openalex.org/S4306400464","display_name":"Research Online (Edith Cowan University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I12079687","host_organization_name":"Edith Cowan University","host_organization_lineage":["https://openalex.org/I12079687"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Research outputs 2022 to 2026","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W42608200","https://openalex.org/W109974757","https://openalex.org/W1674866864","https://openalex.org/W1772650917","https://openalex.org/W1922120546","https://openalex.org/W1970438433","https://openalex.org/W1998910452","https://openalex.org/W2004477950","https://openalex.org/W2077163927","https://openalex.org/W2079854881","https://openalex.org/W2109164068","https://openalex.org/W2117228865","https://openalex.org/W2133775549","https://openalex.org/W2135583584","https://openalex.org/W2138828804","https://openalex.org/W2150066425","https://openalex.org/W2151103935","https://openalex.org/W2165114467","https://openalex.org/W2259424905","https://openalex.org/W2340897893","https://openalex.org/W2440384215","https://openalex.org/W2604231069","https://openalex.org/W2751625733","https://openalex.org/W2770902190","https://openalex.org/W2776033207","https://openalex.org/W2886944874","https://openalex.org/W2889002172","https://openalex.org/W2890417831","https://openalex.org/W2895401575","https://openalex.org/W2911486422","https://openalex.org/W2945016429","https://openalex.org/W2946608878","https://openalex.org/W2948384918","https://openalex.org/W2948647700","https://openalex.org/W2949023359","https://openalex.org/W2952813711","https://openalex.org/W2953804911","https://openalex.org/W2954174912","https://openalex.org/W2963150697","https://openalex.org/W2963231581","https://openalex.org/W2963277791","https://openalex.org/W2963351448","https://openalex.org/W2963496125","https://openalex.org/W2963548592","https://openalex.org/W2963617879","https://openalex.org/W2963619659","https://openalex.org/W2964968086","https://openalex.org/W2980467688","https://openalex.org/W2982809261","https://openalex.org/W2991514044","https://openalex.org/W2997575304","https://openalex.org/W3002430262","https://openalex.org/W3034062331","https://openalex.org/W3034514115","https://openalex.org/W3035749845","https://openalex.org/W3048395011","https://openalex.org/W3090896893","https://openalex.org/W3104104444","https://openalex.org/W3119074118","https://openalex.org/W3135450157","https://openalex.org/W3156697068","https://openalex.org/W3172573759","https://openalex.org/W3176755188","https://openalex.org/W6677548441","https://openalex.org/W6743438356","https://openalex.org/W6764514022","https://openalex.org/W6768191249","https://openalex.org/W6775421375","https://openalex.org/W6779402845"],"related_works":["https://openalex.org/W2092680635","https://openalex.org/W2160589835","https://openalex.org/W2510234973","https://openalex.org/W2017236227","https://openalex.org/W2416752100","https://openalex.org/W1985796632","https://openalex.org/W1770401123","https://openalex.org/W3043596039","https://openalex.org/W4205368567","https://openalex.org/W2531533028"],"abstract_inverted_index":{"Autonomous":[0],"vehicles":[1],"in":[2,58,66,225],"intelligent":[3],"transportation":[4],"systems":[5,33],"must":[6],"be":[7,53,177],"able":[8],"to":[9,97,114],"perform":[10],"reliable":[11],"and":[12,40,125,158,170,179,227],"safe":[13],"navigation.":[14],"This":[15],"necessitates":[16],"accurate":[17],"object":[18],"detection,":[19],"which":[20,203],"is":[21,75,111,195],"commonly":[22],"achieved":[23],"by":[24,117,197,246],"high-precision":[25],"depth":[26,31,56,68,73,101,136,228],"perception.":[27],"Existing":[28],"stereo":[29,108,187],"vision-based":[30],"estimation":[32,41,74,92],"generally":[34],"involve":[35],"computation":[36],"of":[37,42,72,90,100,106,120,138,155,163,185,192,201,208,243],"pixel":[38],"correspondences":[39],"disparities":[43],"between":[44],"rectified":[45],"image":[46],"pairs.":[47],"The":[48,190],"estimated":[49],"disparity":[50,80,91,226],"values":[51,57],"will":[52],"converted":[54],"into":[55],"downstream":[59],"applications.":[60],"As":[61],"most":[62],"applications":[63],"often":[64,76,133],"work":[65],"the":[67,70,88,98,104,118,121,126,130,153,182,186,209,214,240,244],"domain,":[69],"accuracy":[71,89,99],"more":[77],"compelling":[78],"than":[79],"estimation.":[81,102],"However,":[82],"at":[83,143,234],"large":[84,144],"distances":[85,235],"(>":[86],"50m),":[87],"does":[93],"not":[94],"directly":[95],"translate":[96],"In":[103],"context":[105],"learning-based":[107],"systems,":[109],"this":[110,148],"mainly":[112],"due":[113],"biases":[115,157],"imposed":[116],"choices":[119],"disparity-based":[122],"loss":[123,165,174],"function":[124],"training":[127],"data.":[128],"Consequently,":[129],"learning":[131,188],"algorithms":[132],"produce":[134],"unreliable":[135],"estimates":[137],"under-represented":[139],"foreground":[140,168],"objects,":[141],"particularly":[142,230],"distances.":[145],"To":[146],"resolve":[147],"issue,":[149],"we":[150],"first":[151],"analyze":[152],"effect":[154],"those":[156],"then":[159],"propose":[160],"a":[161],"pair":[162],"depth-based":[164],"functions":[166,175],"for":[167,231],"objects":[169,232],"background":[171],"separately.":[172],"These":[173],"can":[176,180],"tuned":[178],"balance":[181],"inherent":[183],"bias":[184],"algorithms.":[189],"efficacy":[191],"our":[193,219],"solution":[194,221],"demonstrated":[196],"an":[198],"extensive":[199],"set":[200],"experiments,":[202],"are":[204],"benchmarked":[205],"against":[206],"state":[207,242],"art.":[210],"We":[211],"show":[212],"on":[213],"KITTI":[215],"2015":[216],"benchmark":[217],"that":[218],"proposed":[220],"yields":[222],"substantial":[223],"improvements":[224],"estimation,":[229],"located":[233],"beyond":[236],"50":[237],"meters,":[238],"outperforming":[239],"previous":[241],"art":[245],"10%.":[247]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T08:27:34.040176","created_date":"2025-10-10T00:00:00"}