{"id":"https://openalex.org/W4206362146","doi":"https://doi.org/10.1145/3469877.3490568","title":"Attention-based Dual-Branches Localization Network for Weakly Supervised Object Localization","display_name":"Attention-based Dual-Branches Localization Network for Weakly Supervised Object Localization","publication_year":2021,"publication_date":"2021-12-01","ids":{"openalex":"https://openalex.org/W4206362146","doi":"https://doi.org/10.1145/3469877.3490568"},"language":"en","primary_location":{"id":"doi:10.1145/3469877.3490568","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469877.3490568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Multimedia Asia","raw_type":"proceedings-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/A5054356164","display_name":"Wenjun Hui","orcid":null},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wenjun Hui","raw_affiliation_strings":["Yanshan University, CN"],"affiliations":[{"raw_affiliation_string":"Yanshan University, CN","institution_ids":["https://openalex.org/I39333907"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078290333","display_name":"Chuangchuang Tan","orcid":"https://orcid.org/0000-0002-9342-1407"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuangchuang Tan","raw_affiliation_strings":["Beijing Jiaotong University, CN"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, CN","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080706260","display_name":"Guanghua Gu","orcid":"https://orcid.org/0000-0002-9532-8273"},"institutions":[{"id":"https://openalex.org/I39333907","display_name":"Yanshan University","ror":"https://ror.org/02txfnf15","country_code":"CN","type":"education","lineage":["https://openalex.org/I39333907"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanghua Gu","raw_affiliation_strings":["Yanshan University, China"],"affiliations":[{"raw_affiliation_string":"Yanshan University, China","institution_ids":["https://openalex.org/I39333907"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5054356164"],"corresponding_institution_ids":["https://openalex.org/I39333907"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18019608,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9934999942779541,"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/discriminative-model","display_name":"Discriminative model","score":0.8617068529129028},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7609292268753052},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7503291368484497},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7059451937675476},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6462895274162292},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.6404687166213989},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5700340270996094},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5397786498069763},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.521213173866272},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4953443109989166},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.46743741631507874},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41797637939453125}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8617068529129028},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7609292268753052},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7503291368484497},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7059451937675476},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6462895274162292},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.6404687166213989},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5700340270996094},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5397786498069763},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.521213173866272},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4953443109989166},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.46743741631507874},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41797637939453125},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3469877.3490568","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3469877.3490568","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Multimedia Asia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7799999713897705,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2117539524","https://openalex.org/W2295107390","https://openalex.org/W2746791238","https://openalex.org/W2913550731","https://openalex.org/W2963045696","https://openalex.org/W2964159923","https://openalex.org/W2991090032","https://openalex.org/W3001083904","https://openalex.org/W3024127982","https://openalex.org/W3103376464","https://openalex.org/W3107169861","https://openalex.org/W3110272085","https://openalex.org/W3176171254","https://openalex.org/W3179079440","https://openalex.org/W3188615767"],"related_works":["https://openalex.org/W3000097931","https://openalex.org/W2354322770","https://openalex.org/W4237547500","https://openalex.org/W1570848052","https://openalex.org/W2373192430","https://openalex.org/W4239268388","https://openalex.org/W4389116644","https://openalex.org/W4243305035","https://openalex.org/W2153315159","https://openalex.org/W1537496349"],"abstract_inverted_index":{"Weakly":[0],"supervised":[1],"object":[2,104],"localization":[3,28],"exploits":[4],"the":[5,14,33,55,133],"last":[6],"convolutional":[7],"feature":[8,25,59,99],"maps":[9,26,100],"of":[10,16],"classification":[11,38],"model":[12],"and":[13,53,77,86,128],"weights":[15,34],"Fully-Connected":[17],"(FC)":[18],"layer":[19],"to":[20,37,44,49,82,101,119],"achieves":[21,136],"localization.":[22],"However,":[23],"high-level":[24],"for":[27,58,89,116],"lack":[29],"edge":[30,51,84,105],"features.":[31],"Additionally,":[32,107],"are":[35,80],"specific":[36],"task,":[39],"causing":[40],"only":[41],"discriminative":[42],"regions":[43],"be":[45],"discovered.":[46],"In":[47],"order":[48],"fuse":[50],"features":[52,85,88,118],"adjust":[54],"attention":[56,78,111,115],"distribution":[57],"map":[60],"channels,":[61],"we":[62],"propose":[63],"an":[64],"efficient":[65],"method":[66,135],"called":[67],"Attention-based":[68],"Dual-Branches":[69],"Localization":[70],"(ADBL)":[71],"Network,":[72],"in":[73],"which":[74],"dual-branches":[75,95],"structure":[76,96],"mechanism":[79,112],"adopted":[81],"mine":[83,102],"non-discriminative":[87,121],"locating":[90],"more":[91],"target":[92,103],"areas.":[93,122],"Specifically,":[94],"cascades":[97],"low-level":[98],"regions.":[106],"during":[108],"inference":[109],"stage,":[110],"assigns":[113],"appropriate":[114],"different":[117],"preserve":[120],"Extensive":[123],"experiments":[124],"on":[125],"both":[126],"ILSVRC":[127],"CUB-200-2011":[129],"datasets":[130],"show":[131],"that":[132],"ADBL":[134],"substantial":[137],"performance":[138],"improvements.":[139]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
