{"id":"https://openalex.org/W4224925019","doi":"https://doi.org/10.1109/icassp43922.2022.9747532","title":"Attention-based Adversarial Partial Domain Adaptation","display_name":"Attention-based Adversarial Partial Domain Adaptation","publication_year":2022,"publication_date":"2022-04-27","ids":{"openalex":"https://openalex.org/W4224925019","doi":"https://doi.org/10.1109/icassp43922.2022.9747532"},"language":"en","primary_location":{"id":"doi:10.1109/icassp43922.2022.9747532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747532","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5057464374","display_name":"Mengzhu Wang","orcid":"https://orcid.org/0000-0002-1059-0441"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengzhu Wang","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021902921","display_name":"Shan An","orcid":"https://orcid.org/0000-0001-7796-6952"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan An","raw_affiliation_strings":["Tech & Data Center JD.COM Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tech & Data Center JD.COM Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100426938","display_name":"Xiao Luo","orcid":"https://orcid.org/0000-0002-7987-3714"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Luo","raw_affiliation_strings":["Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079018005","display_name":"Peng Xiong","orcid":"https://orcid.org/0000-0002-6780-5853"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiong Peng","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100608416","display_name":"Wei Yu","orcid":"https://orcid.org/0000-0002-6740-0485"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Yu","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045191293","display_name":"Junyang Chen","orcid":"https://orcid.org/0000-0002-1139-8654"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junyang Chen","raw_affiliation_strings":["Shenzhen University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen University","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061811574","display_name":"Zhigang Luo","orcid":"https://orcid.org/0000-0002-7552-201X"},"institutions":[{"id":"https://openalex.org/I170215575","display_name":"National University of Defense Technology","ror":"https://ror.org/05d2yfz11","country_code":"CN","type":"education","lineage":["https://openalex.org/I170215575"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhigang Luo","raw_affiliation_strings":["National University of Defense Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National University of Defense Technology","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3144","last_page":"3148"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9620000123977661,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9513000249862671,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8089988231658936},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.763102650642395},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.714065432548523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6437340378761292},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6339563727378845},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.6234259009361267},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.556642472743988},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5187323689460754},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4993746280670166},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.49333539605140686},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4151926636695862},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10559684038162231},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.07691407203674316},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07435718178749084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8089988231658936},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.763102650642395},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.714065432548523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6437340378761292},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6339563727378845},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.6234259009361267},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.556642472743988},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5187323689460754},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4993746280670166},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.49333539605140686},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4151926636695862},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10559684038162231},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.07691407203674316},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07435718178749084},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp43922.2022.9747532","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp43922.2022.9747532","pdf_url":null,"source":{"id":"https://openalex.org/S4363607702","display_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1722318740","https://openalex.org/W1882958252","https://openalex.org/W2104094955","https://openalex.org/W2149298154","https://openalex.org/W2159291411","https://openalex.org/W2194775991","https://openalex.org/W2279034837","https://openalex.org/W2293363371","https://openalex.org/W2593768305","https://openalex.org/W2627183927","https://openalex.org/W2766897166","https://openalex.org/W2795155917","https://openalex.org/W2885722640","https://openalex.org/W2962835731","https://openalex.org/W2962858109","https://openalex.org/W2962986791","https://openalex.org/W3023747762","https://openalex.org/W3102532606","https://openalex.org/W3119158197","https://openalex.org/W3207977952","https://openalex.org/W4206229730","https://openalex.org/W4298289240","https://openalex.org/W6637568146","https://openalex.org/W6639480849","https://openalex.org/W6681588610","https://openalex.org/W6683633756","https://openalex.org/W6695692224","https://openalex.org/W6734871034","https://openalex.org/W6746171285","https://openalex.org/W6750109254","https://openalex.org/W6776460941","https://openalex.org/W6785249861","https://openalex.org/W6787700805"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4394775207","https://openalex.org/W4283211831","https://openalex.org/W3105973526","https://openalex.org/W2798287483"],"abstract_inverted_index":{"With":[0],"the":[1,25,39,99,123,132,147,159],"rapid":[2],"development":[3],"of":[4,76],"vision-based":[5],"deep":[6],"learning":[7],"(DL),":[8],"it":[9,57],"is":[10,47],"an":[11,45,84],"effective":[12],"method":[13,129,149],"to":[14,19,23,68,97,119,130,135],"generate":[15],"large-scale":[16],"synthetic":[17],"data":[18,22],"supplement":[20],"real":[21],"train":[24,131],"DL":[26],"models":[27],"for":[28,51],"domain":[29,34,67,72,88,95,101,116,161],"adaptation.":[30,117],"However,":[31],"previous":[32],"vanilla":[33,115],"adaptation":[35,59,89,96,162],"methods":[36,152],"generally":[37],"assume":[38],"same":[40],"label":[41],"space,":[42],"and":[43,63],"such":[44],"assumption":[46],"no":[48],"longer":[49],"valid":[50],"a":[52,61,69,114,154],"more":[53,64],"realistic":[54],"scenario":[55],"where":[56],"requires":[58],"from":[60],"larger":[62],"diverse":[65],"source":[66,104],"smaller":[70],"target":[71,100],"with":[73],"less":[74],"number":[75],"classes.":[77],"To":[78],"handle":[79],"this":[80,111],"problem,":[81],"we":[82,92,107,126],"propose":[83],"attention-based":[85,128],"adversarial":[86,94,133],"partial":[87],"(AADA).":[90],"Specifically,":[91],"leverage":[93],"augment":[98],"by":[102,153],"using":[103],"domain,":[105],"then":[106],"can":[108],"readily":[109],"turn":[110],"task":[112],"into":[113],"Meanwhile,":[118],"accurately":[120],"focus":[121],"on":[122,142,158],"transferable":[124,138],"features,":[125],"apply":[127],"networks":[134],"obtain":[136],"better":[137],"semantic":[139],"features.":[140],"Experiments":[141],"four":[143],"benchmarks":[144],"demonstrate":[145],"that":[146],"proposed":[148],"outperforms":[150],"existing":[151],"large":[155],"margin,":[156],"especially":[157],"tough":[160],"tasks,":[163],"e.g.":[164],"VisDA-2017.":[165]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}