{"id":"https://openalex.org/W3088172692","doi":"https://doi.org/10.1109/lsp.2020.3025128","title":"Relation R-CNN: A Graph Based Relation-Aware Network for Object Detection","display_name":"Relation R-CNN: A Graph Based Relation-Aware Network for Object Detection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3088172692","doi":"https://doi.org/10.1109/lsp.2020.3025128","mag":"3088172692"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2020.3025128","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3025128","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/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":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":"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":"last","author":{"id":"https://openalex.org/A5087798028","display_name":"Zhenjun Tang","orcid":"https://orcid.org/0000-0003-3664-1363"},"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":"Zhenjun Tang","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"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5006547546"],"corresponding_institution_ids":["https://openalex.org/I29739308"],"apc_list":null,"apc_paid":null,"fwci":4.3171,"has_fulltext":false,"cited_by_count":74,"citation_normalized_percentile":{"value":0.9558012,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"27","issue":null,"first_page":"1680","last_page":"1684"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":1.0,"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":1.0,"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":0.9980999827384949,"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":0.9976000189781189,"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/relation","display_name":"Relation (database)","score":0.7687099575996399},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7145646214485168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.584665834903717},{"id":"https://openalex.org/keywords/pascal","display_name":"Pascal (unit)","score":0.5585280656814575},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5506097078323364},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5384201407432556},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5271216034889221},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5235171914100647},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.4727780818939209},{"id":"https://openalex.org/keywords/spatial-relation","display_name":"Spatial relation","score":0.4682268798351288},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45954081416130066},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4488834738731384},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4300449788570404},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32864683866500854},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.19521686434745789}],"concepts":[{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7687099575996399},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7145646214485168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.584665834903717},{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.5585280656814575},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5506097078323364},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5384201407432556},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5271216034889221},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5235171914100647},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4727780818939209},{"id":"https://openalex.org/C27511587","wikidata":"https://www.wikidata.org/wiki/Q2178623","display_name":"Spatial relation","level":2,"score":0.4682268798351288},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45954081416130066},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4488834738731384},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4300449788570404},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32864683866500854},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.19521686434745789},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2020.3025128","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2020.3025128","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1038957148","display_name":null,"funder_award_id":"61962008","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1153685412","display_name":null,"funder_award_id":"61966004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3744706737","display_name":null,"funder_award_id":"61866004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6096834954","display_name":null,"funder_award_id":"2019GXNSFDA245018","funder_id":"https://openalex.org/F4320322768","funder_display_name":"Natural Science Foundation of Guangxi Province"},{"id":"https://openalex.org/G6141150359","display_name":null,"funder_award_id":"2017GXNSFAA198365","funder_id":"https://openalex.org/F4320322768","funder_display_name":"Natural Science Foundation of Guangxi Province"},{"id":"https://openalex.org/G8026423800","display_name":null,"funder_award_id":"61663004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8133291618","display_name":null,"funder_award_id":"2018GXNSFDA281009","funder_id":"https://openalex.org/F4320322768","funder_display_name":"Natural Science Foundation of Guangxi Province"}],"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":42,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1832500336","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/W2194775991","https://openalex.org/W2277195237","https://openalex.org/W2288122362","https://openalex.org/W2398118205","https://openalex.org/W2519205375","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2579985080","https://openalex.org/W2606609115","https://openalex.org/W2618530766","https://openalex.org/W2740569051","https://openalex.org/W2799215407","https://openalex.org/W2888728082","https://openalex.org/W2889730893","https://openalex.org/W2932399282","https://openalex.org/W2935837427","https://openalex.org/W2939462079","https://openalex.org/W2962835968","https://openalex.org/W2962917547","https://openalex.org/W2963093690","https://openalex.org/W2963858333","https://openalex.org/W2963947444","https://openalex.org/W2964080601","https://openalex.org/W2982112268","https://openalex.org/W3106250896","https://openalex.org/W4285723986","https://openalex.org/W6637373629","https://openalex.org/W6639102338","https://openalex.org/W6732243160","https://openalex.org/W6754502870","https://openalex.org/W6760424586","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W4376620596","https://openalex.org/W3177249605","https://openalex.org/W2534152068","https://openalex.org/W3138508047","https://openalex.org/W1972515067","https://openalex.org/W1689909837","https://openalex.org/W4293054914","https://openalex.org/W4298525700","https://openalex.org/W2953362004","https://openalex.org/W2549121492"],"abstract_inverted_index":{"Due":[0],"to":[1,22,51,66,81,144,185],"the":[2,8,12,37,40,53,68,75,83,97,100,110,112,122,136,165],"deteriorated":[3],"quality":[4],"of":[5,11,39,99,104,138,168],"feature":[6,90,118],"in":[7,72,87,109,182],"propagation":[9],"process":[10],"neural":[13],"network,":[14,50,111],"it":[15],"may":[16],"be":[17],"hard":[18],"for":[19],"traditional":[20,41],"detector":[21],"identify":[23],"a":[24,46],"small":[25,146,169],"object":[26,42,139],"by":[27,95,177],"just":[28],"utilizing":[29],"information":[30,55,133],"within":[31],"one":[32],"region":[33],"proposal.":[34],"To":[35],"overcome":[36],"limitation":[38],"detector,":[43],"we":[44],"proposed":[45,65,80],"graph":[47],"based":[48],"relation-aware":[49,113],"capture":[52,82],"relation":[54,62,71,77,86,132],"from":[56,171],"labels,":[57,73],"and":[58,74,125,148,174,179],"images.":[59,88],"The":[60,89,152],"semantic":[61,70],"network":[63,78,114],"is":[64,79,92],"mine":[67],"global":[69],"spatial":[76,85],"local":[84],"representation":[91],"further":[93],"improved":[94],"aggregating":[96],"outputs":[98],"two":[101],"networks.":[102],"Instead":[103],"directly":[105],"disseminating":[106],"visual":[107],"features":[108],"explores":[115],"more":[116],"advanced":[117],"information.":[119],"Experiments":[120],"on":[121,154],"PASCAL":[123],"VOC,":[124],"MS":[126],"COCO":[127,155],"datasets":[128],"demonstrate":[129,157],"that":[130],"key":[131],"significantly":[134],"improve":[135],"performance":[137,167,183],"detection":[140,166],"with":[141],"better":[142],"ability":[143],"detect":[145,161],"objects,":[147],"reasonable":[149],"bounding":[150],"box.":[151],"results":[153],"dataset":[156],"our":[158],"method":[159],"can":[160],"objects":[162,170],"robustly,":[163],"increasing":[164],"average":[172,175],"precision,":[173],"recall":[176],"31.8%,":[178],"32.3%":[180],"respectively":[181],"relative":[184],"Faster":[186],"R-CNN.":[187]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":21},{"year":2023,"cited_by_count":29},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":6}],"updated_date":"2026-03-29T08:15:47.926485","created_date":"2025-10-10T00:00:00"}