{"id":"https://openalex.org/W4413267659","doi":"https://doi.org/10.1109/tce.2025.3593332","title":"MonoTrans: Long-Range Contextual Dependency Transformer for Monocular 3-D Object Detection","display_name":"MonoTrans: Long-Range Contextual Dependency Transformer for Monocular 3-D Object Detection","publication_year":2025,"publication_date":"2025-07-28","ids":{"openalex":"https://openalex.org/W4413267659","doi":"https://doi.org/10.1109/tce.2025.3593332"},"language":"en","primary_location":{"id":"doi:10.1109/tce.2025.3593332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3593332","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","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/A5103683114","display_name":"Yan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yan Li","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0009-0006-3191-0244","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102201087","display_name":"Xuan Liu","orcid":"https://orcid.org/0009-0006-2635-911X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuan Liu","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012624002","display_name":"Zexi Hua","orcid":"https://orcid.org/0000-0001-6263-1869"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ze-Xi Hua","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-6263-1869","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061722604","display_name":"Zi-Wei Sun","orcid":"https://orcid.org/0000-0001-6067-0514"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zi-Wei Sun","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-6067-0514","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103683114"],"corresponding_institution_ids":["https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18553729,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"71","issue":"3","first_page":"7570","last_page":"7583"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9901000261306763,"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/computer-science","display_name":"Computer science","score":0.5870940089225769},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.5443441867828369},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.4800201952457428},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4571949541568756},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4367259740829468},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41267600655555725},{"id":"https://openalex.org/keywords/electrical-engineering","display_name":"Electrical engineering","score":0.24024033546447754},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23100531101226807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.19346770644187927},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.1664048135280609}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5870940089225769},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.5443441867828369},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.4800201952457428},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4571949541568756},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4367259740829468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41267600655555725},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.24024033546447754},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23100531101226807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.19346770644187927},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.1664048135280609}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tce.2025.3593332","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2025.3593332","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"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 Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7164170120","display_name":null,"funder_award_id":"2020YFB1711902","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2560544142","https://openalex.org/W3035254347","https://openalex.org/W3096609285","https://openalex.org/W3138516171","https://openalex.org/W3156216502","https://openalex.org/W3169690993","https://openalex.org/W3172261075","https://openalex.org/W3173668541","https://openalex.org/W3175233244","https://openalex.org/W3176319743","https://openalex.org/W3195714131","https://openalex.org/W3204439495","https://openalex.org/W3204445544","https://openalex.org/W3217060323","https://openalex.org/W4200629618","https://openalex.org/W4200632008","https://openalex.org/W4225282965","https://openalex.org/W4226085288","https://openalex.org/W4281606129","https://openalex.org/W4310078553","https://openalex.org/W4312713480","https://openalex.org/W4312842574","https://openalex.org/W4313053541","https://openalex.org/W4313059105","https://openalex.org/W4319300623","https://openalex.org/W4385245566","https://openalex.org/W4386066137","https://openalex.org/W4389640508","https://openalex.org/W4390813021","https://openalex.org/W4390873008","https://openalex.org/W4402704555"],"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":{"Monocular":[0],"3D":[1,18,167],"object":[2,168],"detection":[3],"has":[4],"attracted":[5],"widespread":[6],"attention":[7],"due":[8],"to":[9,55,163],"its":[10],"simplicity":[11],"and":[12,59,102,124,135,148,161,175],"low":[13],"cost.":[14],"However,":[15],"accurately":[16],"localizing":[17],"objects":[19],"from":[20],"a":[21,28,79],"single":[22],"image":[23],"without":[24,185],"depth":[25,45,50,65,90,99,146,154],"information":[26,66,70,91,100,155],"is":[27],"highly":[29],"challenging":[30],"problem.":[31],"Many":[32],"existing":[33,165],"methods":[34],"use":[35],"only":[36],"local":[37],"visual":[38],"features":[39,126],"for":[40,116],"simple":[41],"aggregation":[42],"of":[43,64,86,98,106,127],"multiple":[44,145],"predictions,":[46],"ignoring":[47],"the":[48,62,69,89,96,104,110,119,142,173],"long-range":[49,111],"dependencies":[51,150],"between":[52,121,144],"objects,":[53],"failing":[54],"utilize":[56],"global":[57],"information,":[58],"not":[60],"considering":[61],"problem":[63,97],"loss":[67,101],"in":[68],"extraction":[71,105],"process.":[72],"To":[73],"alleviate":[74],"this":[75],"problem,":[76],"we":[77],"propose":[78],"novel":[80],"framework,":[81],"MonoTrans.":[82],"It":[83],"mainly":[84],"consists":[85],"two":[87],"components,":[88],"enhancement":[92,156],"module,":[93],"which":[94],"solves":[95],"improves":[103],"model":[107],"depth-aware":[108,125],"features;":[109],"contextual":[112],"dependency":[113],"fusion":[114,123],"module":[115,157],"effective":[117],"modeling":[118],"relationship":[120],"context":[122],"different":[128],"depth-estimated":[129],"feature":[130],"values":[131],"through":[132],"deep":[133],"cross-attention":[134],"window-shift":[136],"spatial":[137],"self-attention,":[138],"thereby":[139],"fully":[140],"exploiting":[141],"interactions":[143],"cues":[147],"capturing":[149],"information.":[151,188],"Furthermore,":[152],"our":[153,180],"can":[158],"be":[159],"lightweight":[160],"plug-and-play":[162],"enhance":[164],"monocular":[166],"detectors.":[169],"Extensive":[170],"experiments":[171],"on":[172],"KITTI":[174],"Waymo":[176],"datasets":[177],"demonstrate":[178],"that":[179],"method":[181],"achieves":[182],"state-of-the-art":[183],"performance":[184],"introducing":[186],"extra":[187]},"counts_by_year":[],"updated_date":"2025-12-28T23:10:05.387466","created_date":"2025-10-10T00:00:00"}
