{"id":"https://openalex.org/W4413017869","doi":"https://doi.org/10.1109/tase.2025.3596395","title":"Domain Adaptation With Generated Infrared Images for Multi-Spectra Pedestrian Detection","display_name":"Domain Adaptation With Generated Infrared Images for Multi-Spectra Pedestrian Detection","publication_year":2025,"publication_date":"2025-08-06","ids":{"openalex":"https://openalex.org/W4413017869","doi":"https://doi.org/10.1109/tase.2025.3596395"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2025.3596395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3596395","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Automation Science and Engineering","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/A5101654841","display_name":"Lu Ding","orcid":"https://orcid.org/0000-0002-6316-8527"},"institutions":[{"id":"https://openalex.org/I150807315","display_name":"Guangxi University","ror":"https://ror.org/02c9qn167","country_code":"CN","type":"education","lineage":["https://openalex.org/I150807315"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lu Ding","raw_affiliation_strings":["School of Electrical Engineering, Guangxi University, Nanning, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering, Guangxi University, Nanning, China","institution_ids":["https://openalex.org/I150807315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002543242","display_name":"Lei Song","orcid":"https://orcid.org/0000-0002-9401-3798"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]},{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Song","raw_affiliation_strings":["School of Automation and Intelligent Sensing and the School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China","School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Automation and Intelligent Sensing and the School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I9842412"]},{"raw_affiliation_string":"School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101846774","display_name":"Dan Huang","orcid":"https://orcid.org/0000-0001-6468-4956"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Huang","raw_affiliation_strings":["School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100454382","display_name":"Yong Chen","orcid":"https://orcid.org/0000-0002-0279-9405"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Chen","raw_affiliation_strings":["School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101654841"],"corresponding_institution_ids":["https://openalex.org/I150807315"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23003425,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"23","issue":null,"first_page":"3673","last_page":"3682"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9811999797821045,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9811999797821045,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9591000080108643,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9437999725341797,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/pedestrian-detection","display_name":"Pedestrian detection","score":0.6668443083763123},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5675109028816223},{"id":"https://openalex.org/keywords/infrared","display_name":"Infrared","score":0.556665301322937},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5387654304504395},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49939751625061035},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.42877593636512756},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.4201139509677887},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37306535243988037},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.3452109098434448},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23413071036338806},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.2196466326713562},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.20670568943023682},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.115820974111557},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.08701899647712708}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.6668443083763123},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5675109028816223},{"id":"https://openalex.org/C158355884","wikidata":"https://www.wikidata.org/wiki/Q11388","display_name":"Infrared","level":2,"score":0.556665301322937},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5387654304504395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49939751625061035},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.42877593636512756},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.4201139509677887},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37306535243988037},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3452109098434448},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23413071036338806},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.2196466326713562},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.20670568943023682},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.115820974111557},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.08701899647712708}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2025.3596395","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2025.3596395","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.4699999988079071,"display_name":"Sustainable cities and communities"}],"awards":[{"id":"https://openalex.org/G1107487223","display_name":null,"funder_award_id":"GuiKe23026264","funder_id":"https://openalex.org/F4320336630","funder_display_name":"Specific Research Project of Guangxi for Research Bases and Talents"},{"id":"https://openalex.org/G5215680313","display_name":null,"funder_award_id":"2025GXNSFBA069285","funder_id":"https://openalex.org/F4320313613","funder_display_name":"Natural Science Foundation of Guangxi Zhuang Autonomous Region"}],"funders":[{"id":"https://openalex.org/F4320313613","display_name":"Natural Science Foundation of Guangxi Zhuang Autonomous Region","ror":null},{"id":"https://openalex.org/F4320335669","display_name":"Key Laboratory of System Control and Information Processing","ror":null},{"id":"https://openalex.org/F4320336630","display_name":"Specific Research Project of Guangxi for Research Bases and Talents","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2068124150","https://openalex.org/W2565639579","https://openalex.org/W2593768305","https://openalex.org/W2743197123","https://openalex.org/W2789621390","https://openalex.org/W2889151341","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2964115968","https://openalex.org/W2968634921","https://openalex.org/W2971938076","https://openalex.org/W3035175896","https://openalex.org/W3096831136","https://openalex.org/W3104978563","https://openalex.org/W3116967329","https://openalex.org/W3143918648","https://openalex.org/W3160361512","https://openalex.org/W3163617518","https://openalex.org/W3166409449","https://openalex.org/W3180975139","https://openalex.org/W3195903836","https://openalex.org/W3213472242","https://openalex.org/W3217181497","https://openalex.org/W4214623799","https://openalex.org/W4220724622","https://openalex.org/W4285142937","https://openalex.org/W4293222296","https://openalex.org/W4318570584","https://openalex.org/W4323666945","https://openalex.org/W4385728398","https://openalex.org/W4386363015","https://openalex.org/W4388206493","https://openalex.org/W4392655270","https://openalex.org/W4393171196","https://openalex.org/W4393198799"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W3122828758","https://openalex.org/W2101960027","https://openalex.org/W4205958986","https://openalex.org/W2197846993","https://openalex.org/W49697837","https://openalex.org/W2586575957","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"To":[0],"fully":[1],"utilize":[2],"the":[3,30,40,43,47,50,58,62,71,103,111,115,123,126,143,165,173],"knowledge":[4],"in":[5],"visible":[6],"and":[7,10,46,89,91,96,135,151,168,172,180],"infrared":[8,15],"images":[9,38,129],"perform":[11],"pedestrian":[12,24,63,116,154],"detection":[13,25],"on":[14,149],"images,":[16],"we":[17,28,121],"propose":[18],"a":[19,131],"multi-level":[20],"multi-source":[21],"domain":[22,45,52,94,98,128],"adaptive":[23],"method.":[26],"Firstly,":[27],"use":[29],"Generative":[31],"Adversarial":[32],"Network":[33],"(GAN)":[34],"method":[35,160],"to":[36,56,60,87,102,141],"generate":[37],"with":[39,65],"content":[41],"of":[42,49,73,82,106,125],"source":[44],"style":[48],"target":[51,127],"as":[53],"additional":[54],"domains":[55],"promote":[57],"model":[59,134,145],"learn":[61,114],"features":[64,84,108,117],"multi-domain":[66],"invariance,":[67],"thereby":[68],"effectively":[69],"alleviating":[70],"problem":[72],"feature":[74],"distribution":[75],"differences":[76],"between":[77],"domains.":[78],"Next,":[79],"different":[80],"scales":[81],"regional":[83],"are":[85,100],"extracted":[86],"fuse":[88],"join,":[90],"then":[92],"image-level":[93],"adaptation":[95,99],"instance-level":[97],"performed":[101],"multi-scale":[104],"part":[105],"region":[107],"so":[109],"that":[110,157],"network":[112],"can":[113],"more":[118],"comprehensively.":[119],"Finally,":[120],"obtain":[122],"prediction":[124],"by":[130,178],"certain":[132],"trained":[133],"make":[136],"it":[137],"into":[138],"pseudo":[139],"labels":[140],"enhance":[142],"subsequent":[144],"training.":[146],"Experimental":[147],"results":[148,163],"KAIST":[150],"LLVIP":[152],"multi-spectral":[153],"datasets":[155],"show":[156],"our":[158],"proposed":[159],"obtains":[161],"better":[162],"than":[164],"baseline":[166],"detector":[167],"other":[169],"existing":[170],"works,":[171],"missing":[174],"rate":[175],"is":[176],"reduced":[177],"3.0%":[179],"3.37%":[181],"respectively.":[182]},"counts_by_year":[],"updated_date":"2026-02-12T06:13:03.167441","created_date":"2025-10-10T00:00:00"}