{"id":"https://openalex.org/W3162600796","doi":"https://doi.org/10.1109/icpr48806.2021.9412825","title":"Object Detection Using Dual Graph Network","display_name":"Object Detection Using Dual Graph Network","publication_year":2021,"publication_date":"2021-01-10","ids":{"openalex":"https://openalex.org/W3162600796","doi":"https://doi.org/10.1109/icpr48806.2021.9412825","mag":"3162600796"},"language":"en","primary_location":{"id":"doi:10.1109/icpr48806.2021.9412825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","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/A5006547546","display_name":"Shengjia Chen","orcid":"https://orcid.org/0000-0002-8083-7905"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shengjia Chen","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100701695","display_name":"Zhixin Li","orcid":"https://orcid.org/0000-0002-5313-6134"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixin Li","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028931239","display_name":"Feicheng Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feicheng Huang","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016469515","display_name":"Canlong Zhang","orcid":"https://orcid.org/0000-0003-4375-1405"},"institutions":[{"id":"https://openalex.org/I29739308","display_name":"Guangxi Normal University","ror":"https://ror.org/02frt9q65","country_code":"CN","type":"education","lineage":["https://openalex.org/I29739308"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Canlong Zhang","raw_affiliation_strings":["Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China"],"affiliations":[{"raw_affiliation_string":"Guangxi Key Lab of Multi-source Information Mining and Security, Guangxi Normal University, Guilin, China","institution_ids":["https://openalex.org/I29739308"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053794277","display_name":"Huifang Ma","orcid":"https://orcid.org/0000-0002-5104-8982"},"institutions":[{"id":"https://openalex.org/I68986083","display_name":"Northwest Normal University","ror":"https://ror.org/00gx3j908","country_code":"CN","type":"education","lineage":["https://openalex.org/I68986083"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huifang Ma","raw_affiliation_strings":["College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou, China","institution_ids":["https://openalex.org/I68986083"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5006547546"],"corresponding_institution_ids":["https://openalex.org/I29739308"],"apc_list":null,"apc_paid":null,"fwci":0.4803,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.63851307,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3280","last_page":"3287"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9995999932289124,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995999932289124,"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":0.752493679523468},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5516036748886108},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5234750509262085},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.34829264879226685},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28493496775627136}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.752493679523468},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5516036748886108},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5234750509262085},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.34829264879226685},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28493496775627136},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr48806.2021.9412825","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr48806.2021.9412825","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 25th International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:ir.lzu.edu.cn/:262010/451463","is_oa":false,"landing_page_url":"http://ir.lzu.edu.cn/handle/262010/451463","pdf_url":null,"source":{"id":"https://openalex.org/S4406923049","display_name":"Lanzhou University Institutional Repository","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"IEEE Conferences"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2312733747","display_name":null,"funder_award_id":"2019GXNSFDA245018,2018GXNSFDA281009,2017GXNSFAA198365","funder_id":"https://openalex.org/F4320322768","funder_display_name":"Natural Science Foundation of Guangxi Province"},{"id":"https://openalex.org/G3928979986","display_name":null,"funder_award_id":"61966004,61663004,61866004,61762078","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322768","display_name":"Natural Science Foundation of Guangxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2102605133","https://openalex.org/W2117287331","https://openalex.org/W2141364309","https://openalex.org/W2163605009","https://openalex.org/W2288122362","https://openalex.org/W2398118205","https://openalex.org/W2519205375","https://openalex.org/W2519887557","https://openalex.org/W2570343428","https://openalex.org/W2606609115","https://openalex.org/W2613718673","https://openalex.org/W2618530766","https://openalex.org/W2740569051","https://openalex.org/W2799215407","https://openalex.org/W2889730893","https://openalex.org/W2894299524","https://openalex.org/W2935837427","https://openalex.org/W2948519073","https://openalex.org/W2962917547","https://openalex.org/W2963093690","https://openalex.org/W2963150697","https://openalex.org/W2963813458","https://openalex.org/W2963858333","https://openalex.org/W2963947444","https://openalex.org/W2964015378","https://openalex.org/W2964080601","https://openalex.org/W3106250896","https://openalex.org/W4297733535","https://openalex.org/W6639102338","https://openalex.org/W6726790931","https://openalex.org/W6754502870","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W3107474891","https://openalex.org/W2000227345","https://openalex.org/W2158065114","https://openalex.org/W2352337710","https://openalex.org/W3087617596","https://openalex.org/W4317655900","https://openalex.org/W2107367999","https://openalex.org/W2391817034","https://openalex.org/W2801014462","https://openalex.org/W4308148751"],"abstract_inverted_index":{"Most":[0],"object":[1,64,132],"detection":[2,40,204],"methods":[3],"focus":[4],"only":[5],"on":[6,43,88,186,218,228],"the":[7,11,16,58,63,68,89,96,105,117,120,125,131,148,151,161,163,172,174,187,201],"local":[8,22,69,135],"information":[9,61,71,137,198],"near":[10],"region":[12,183],"proposal":[13],"and":[14,21,32,67,82,101,124,129,182,190,212],"ignore":[15],"object's":[17],"global":[18,59,80],"semantic":[19,60,110],"relation":[20,24,51,75,114,118,122,197],"spatial":[23,70,113],"information,":[25,170],"resulting":[26],"in":[27,65,72,160,180,230],"limited":[28],"performance.":[29],"To":[30],"capture":[31],"explore":[33],"these":[34],"important":[35],"relations,":[36],"we":[37],"propose":[38],"a":[39,44,85],"method":[41,223],"based":[42],"graph":[45,52,87],"convolutional":[46],"network":[47,115,165],"(GCN).":[48],"Two":[49],"independent":[50],"networks":[53,76],"are":[54],"used":[55],"to":[56,104,107,176,208],"obtain":[57,108,177],"of":[62,99,150,155,203,232],"labels":[66,100,181],"images.":[73],"Semantic":[74],"can":[77],"implicitly":[78],"acquire":[79],"knowledge,":[81],"by":[83,95,119,146],"constructing":[84],"directed":[86],"dataset,":[90],"each":[91],"node":[92],"is":[93,143],"represented":[94],"word":[97],"embedding":[98],"then":[102],"sent":[103],"GCN":[106],"high-level":[109],"representation.":[111],"The":[112,140,216],"encodes":[116],"positional":[121],"module":[123],"visual":[126,158],"connection":[127],"module,":[128],"enriches":[130],"features":[133,159],"through":[134],"key":[136,178,196],"from":[138],"objects.":[139,234],"feature":[141,169],"representation":[142],"further":[144],"improved":[145],"aggregating":[147],"outputs":[149],"two":[152],"networks.":[153],"Instead":[154],"directly":[156],"disseminating":[157],"network,":[162],"dual-graph":[164],"explores":[166],"more":[167],"advanced":[168],"giving":[171],"detector":[173],"ability":[175,207],"relations":[179],"proposals.":[184],"Experiments":[185],"PASCAL":[188],"VOC":[189],"MS":[191],"COCO":[192,219],"datasets":[193],"demonstrate":[194,221],"that":[195],"significantly":[199],"improve":[200],"performance":[202],"with":[205],"better":[206],"detect":[209],"small":[210,233],"objects":[211],"reasonable":[213],"boduning":[214],"box.":[215],"results":[217],"dataset":[220],"our":[222],"obtains":[224],"around":[225],"32.3%":[226],"improvement":[227],"AP":[229],"terms":[231]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
