{"id":"https://openalex.org/W7128431112","doi":"https://doi.org/10.1109/tits.2026.3652840","title":"MonoRange: Monocular 3-D Object Detection Based on Object-Centric Range Map in Adverse Weather Conditions","display_name":"MonoRange: Monocular 3-D Object Detection Based on Object-Centric Range Map in Adverse Weather Conditions","publication_year":2026,"publication_date":"2026-02-09","ids":{"openalex":"https://openalex.org/W7128431112","doi":"https://doi.org/10.1109/tits.2026.3652840"},"language":null,"primary_location":{"id":"doi:10.1109/tits.2026.3652840","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2026.3652840","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/A5044479047","display_name":"Jae Hyun Yoon","orcid":"https://orcid.org/0000-0002-4993-2496"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae Hyun Yoon","raw_affiliation_strings":["Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024382908","display_name":"Jong Won Jung","orcid":"https://orcid.org/0009-0003-9841-9773"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jong Won Jung","raw_affiliation_strings":["Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Republic of Korea"],"raw_orcid":"https://orcid.org/0009-0003-9841-9773","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I111277659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046704537","display_name":"Seok Bong Yoo","orcid":"https://orcid.org/0000-0002-6528-701X"},"institutions":[{"id":"https://openalex.org/I111277659","display_name":"Chonnam National University","ror":"https://ror.org/05kzjxq56","country_code":"KR","type":"education","lineage":["https://openalex.org/I111277659"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seok Bong Yoo","raw_affiliation_strings":["Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Republic of Korea"],"raw_orcid":"https://orcid.org/0000-0002-6528-701X","affiliations":[{"raw_affiliation_string":"Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Republic of Korea","institution_ids":["https://openalex.org/I111277659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I111277659"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.1365849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"27","issue":"5","first_page":"6121","last_page":"6133"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.803600013256073,"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":0.803600013256073,"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":0.060600001364946365,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.04600000008940697,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7088000178337097},{"id":"https://openalex.org/keywords/adverse-weather","display_name":"Adverse weather","score":0.6340000033378601},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6195999979972839},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5882999897003174},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5109000205993652},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.49410000443458557},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47269999980926514},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.4715000092983246}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7556999921798706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7516999840736389},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7088000178337097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6689000129699707},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.6340000033378601},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6195999979972839},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5882999897003174},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5109000205993652},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47269999980926514},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4715000092983246},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.47099998593330383},{"id":"https://openalex.org/C158829959","wikidata":"https://www.wikidata.org/wiki/Q1640606","display_name":"Monocular vision","level":2,"score":0.43070000410079956},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4189000129699707},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.3528999984264374},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.33329999446868896},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.33309999108314514},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.321399986743927},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.31139999628067017},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C87133666","wikidata":"https://www.wikidata.org/wiki/Q1161699","display_name":"Dynamic range","level":2,"score":0.26919999718666077}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2026.3652840","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2026.3652840","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6616649627685547}],"awards":[{"id":"https://openalex.org/G8132207299","display_name":null,"funder_award_id":"P0020536","funder_id":"https://openalex.org/F4320322064","funder_display_name":"Korea Institute for Advancement of Technology"}],"funders":[{"id":"https://openalex.org/F4320322064","display_name":"Korea Institute for Advancement of Technology","ror":"https://ror.org/015w1qa96"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":71,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2252355370","https://openalex.org/W2950689937","https://openalex.org/W2954174912","https://openalex.org/W2963323244","https://openalex.org/W2999947750","https://openalex.org/W3004135102","https://openalex.org/W3034543232","https://openalex.org/W3035254347","https://openalex.org/W3035713416","https://openalex.org/W3138340105","https://openalex.org/W3138808092","https://openalex.org/W3148242781","https://openalex.org/W3170984066","https://openalex.org/W3172261075","https://openalex.org/W3173668541","https://openalex.org/W3176319743","https://openalex.org/W3176821088","https://openalex.org/W3194523157","https://openalex.org/W3215632849","https://openalex.org/W4200629618","https://openalex.org/W4210435474","https://openalex.org/W4221161773","https://openalex.org/W4225672218","https://openalex.org/W4281480933","https://openalex.org/W4285268314","https://openalex.org/W4285605794","https://openalex.org/W4292622325","https://openalex.org/W4312373367","https://openalex.org/W4312461898","https://openalex.org/W4312596674","https://openalex.org/W4312713480","https://openalex.org/W4312865155","https://openalex.org/W4313192011","https://openalex.org/W4317496742","https://openalex.org/W4320235691","https://openalex.org/W4320401882","https://openalex.org/W4323338596","https://openalex.org/W4364375451","https://openalex.org/W4367281358","https://openalex.org/W4383066401","https://openalex.org/W4383109109","https://openalex.org/W4385975752","https://openalex.org/W4386076667","https://openalex.org/W4386226736","https://openalex.org/W4387757653","https://openalex.org/W4387807184","https://openalex.org/W4388517019","https://openalex.org/W4390873008","https://openalex.org/W4390874447","https://openalex.org/W4392045686","https://openalex.org/W4392903388","https://openalex.org/W4399881121","https://openalex.org/W4400772502","https://openalex.org/W4401236007","https://openalex.org/W4401634204","https://openalex.org/W4402033105","https://openalex.org/W4402704555","https://openalex.org/W4402704610","https://openalex.org/W4402727359","https://openalex.org/W4402816547","https://openalex.org/W4403841936","https://openalex.org/W4403998560","https://openalex.org/W4404059357","https://openalex.org/W4405775322","https://openalex.org/W4406457520","https://openalex.org/W4407638147","https://openalex.org/W4409057731","https://openalex.org/W4409326045","https://openalex.org/W4413219507","https://openalex.org/W4415798895"],"related_works":[],"abstract_inverted_index":{"Monocular":[0],"3D":[1,63,126,144,152,167],"object":[2,64,153,168],"detection":[3,53,65,81,169],"has":[4],"been":[5],"studied":[6],"as":[7,15,47],"a":[8,61,111],"promising":[9],"task":[10],"for":[11],"diverse":[12,40,158],"applications,":[13],"such":[14,46],"autonomous":[16],"driving,":[17],"due":[18],"to":[19,148],"its":[20],"lower":[21],"cost":[22],"and":[23,50,71,121,124,143,150],"more":[24],"straightforward":[25],"configuration":[26],"than":[27],"multiple":[28],"sensors.":[29],"However,":[30],"existing":[31,165],"studies":[32],"have":[33],"focused":[34],"on":[35,157],"clear":[36],"weather":[37,41,76,100,105,159],"without":[38],"considering":[39],"conditions":[42],"with":[43,110],"varying":[44],"intensity,":[45],"rain,":[48],"snow,":[49],"fog,":[51],"affecting":[52],"performance.":[54],"In":[55],"this":[56],"paper,":[57],"we":[58],"propose":[59],"MonoRange,":[60],"monocular":[62,166],"method":[66],"that":[67,162],"uses":[68],"object-centric":[69,91],"images":[70,88,103],"range":[72,85,92,119,131],"maps":[73,86],"in":[74,102],"adverse":[75,99],"conditions.":[77],"Leveraging":[78],"the":[79,118,130,136],"2D":[80,142],"results,":[82],"MonoRange":[83,96,116,163],"generates":[84],"from":[87],"via":[89,104,129],"an":[90],"map":[93,120,132],"reconstruction.":[94],"Furthermore,":[95],"flexibly":[97],"removes":[98],"noise":[101],"intensity":[106],"adaptive":[107],"image":[108,123],"restoration":[109],"weight":[112],"modulation":[113],"transformer.":[114],"Then,":[115],"fuses":[117],"restored":[122],"predicts":[125],"bounding":[127],"boxes":[128,145],"aligned":[133],"detector.":[134],"Introducing":[135],"projected":[137],"box":[138],"consistency":[139],"loss":[140],"between":[141],"also":[146],"enables":[147],"consistent":[149],"accurate":[151],"detection.":[154],"Experimental":[155],"results":[156],"datasets":[160],"demonstrate":[161],"surpasses":[164],"approaches.":[170],"The":[171],"source":[172],"code":[173],"is":[174],"available":[175],"athttps://github.com/jhyoon964/MonoRange":[176]},"counts_by_year":[],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2026-02-10T00:00:00"}
