{"id":"https://openalex.org/W3167129341","doi":"https://doi.org/10.1145/3447587.3447592","title":"A Few Shot Object Detection Method Based on Feature Pyramid Network and Graph Neural Network","display_name":"A Few Shot Object Detection Method Based on Feature Pyramid Network and Graph Neural Network","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3167129341","doi":"https://doi.org/10.1145/3447587.3447592","mag":"3167129341"},"language":"en","primary_location":{"id":"doi:10.1145/3447587.3447592","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447587.3447592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Image and Graphics Processing","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/A5056076367","display_name":"Xinlong Li","orcid":null},"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":true,"raw_author_name":"Xinlong Li","raw_affiliation_strings":["College of Intelligence Science and Technology National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101820263","display_name":"Xingwei Li","orcid":"https://orcid.org/0000-0002-4671-6093"},"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":"Xingwei Li","raw_affiliation_strings":["College of Intelligence Science and Technology National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025597777","display_name":"Jiating Jin","orcid":null},"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":"Jiating Jin","raw_affiliation_strings":["College of Intelligence Science and Technology National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008138556","display_name":"Shaojie Guan","orcid":null},"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":"Shaojie Guan","raw_affiliation_strings":["College of Intelligence Science and Technology National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084460827","display_name":"Yizhi Ge","orcid":null},"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":"Yizhi Ge","raw_affiliation_strings":["College of Intelligence Science and Technology National University of Defense Technology, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence Science and Technology National University of Defense Technology, China","institution_ids":["https://openalex.org/I170215575"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5056076367"],"corresponding_institution_ids":["https://openalex.org/I170215575"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06750945,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"31","last_page":"37"},"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":0.9994999766349792,"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"}},"topics":[{"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9966999888420105,"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":0.9860000014305115,"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/subnet","display_name":"Subnet","score":0.9675589799880981},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7657273411750793},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7474666833877563},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6424453854560852},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6068868637084961},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5447938442230225},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5293707847595215},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5037545561790466},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4884170889854431},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4536745250225067},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.4359617829322815},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43435633182525635},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.43037599325180054},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10325664281845093}],"concepts":[{"id":"https://openalex.org/C21099817","wikidata":"https://www.wikidata.org/wiki/Q7631721","display_name":"Subnet","level":2,"score":0.9675589799880981},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7657273411750793},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7474666833877563},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6424453854560852},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6068868637084961},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5447938442230225},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5293707847595215},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5037545561790466},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4884170889854431},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4536745250225067},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.4359617829322815},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43435633182525635},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.43037599325180054},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10325664281845093},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3447587.3447592","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447587.3447592","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 The 4th International Conference on Image and Graphics Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1483870316","https://openalex.org/W2407521645","https://openalex.org/W2565639579","https://openalex.org/W2601450892","https://openalex.org/W2768228940","https://openalex.org/W2768489488","https://openalex.org/W2808388233","https://openalex.org/W2943605315","https://openalex.org/W2963037989","https://openalex.org/W2964105864","https://openalex.org/W2964749571","https://openalex.org/W2982593143","https://openalex.org/W2989604896","https://openalex.org/W3034974675","https://openalex.org/W3091905774","https://openalex.org/W6717697761","https://openalex.org/W6730903564","https://openalex.org/W6732243160","https://openalex.org/W6735236233","https://openalex.org/W6745836177","https://openalex.org/W6748561909","https://openalex.org/W6748931594","https://openalex.org/W6753494528","https://openalex.org/W6757804589","https://openalex.org/W6760555867","https://openalex.org/W6761108903","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2102539527","https://openalex.org/W2131631951","https://openalex.org/W2356206668","https://openalex.org/W2130707537","https://openalex.org/W3200778902","https://openalex.org/W1977409556","https://openalex.org/W2361602549","https://openalex.org/W4362683600","https://openalex.org/W2105155969","https://openalex.org/W4394867575"],"abstract_inverted_index":{"Few":[0,14],"shot":[1,15,49,123,142],"learning":[2],"has":[3,18],"become":[4],"a":[5,19,47,91,162],"research":[6,39],"focus":[7],"in":[8,23,34,167],"the":[9,62,71,83,100,103,121,131,140,155,173],"field":[10],"of":[11,55,87,106,165],"computer":[12],"vision.":[13],"detection":[16,51,64,143],"method":[17,80,95,160],"very":[20],"crucial":[21],"value":[22],"practice.":[24],"But":[25],"so":[26],"far,":[27],"only":[28,68],"few":[29,48,122,141],"results":[30],"have":[31],"been":[32],"achieved":[33],"this":[35,43],"field,":[36],"and":[37,170],"more":[38],"is":[40,61,67,120,127],"required.":[41],"In":[42],"paper,":[44],"we":[45],"proposed":[46,97],"object":[50,63,72],"method,":[52],"which":[53,66,126],"consists":[54],"two":[56],"subnets.":[57],"The":[58,117],"first":[59],"subnet":[60,119,144],"subnet,":[65,125],"responsible":[69],"for":[70],"positioning.":[73],"We":[74],"adopted":[75],"an":[76],"anchor":[77,88],"box":[78],"clustering":[79],"to":[81,98,129,139,145],"produce":[82],"proper":[84],"initial":[85],"size":[86],"boxes.":[89],"Furthermore,":[90],"general":[92],"class":[93],"classification":[94,124],"was":[96],"make":[99],"model":[101],"learn":[102],"common":[104],"features":[105],"different":[107],"classes.":[108],"Therefore,":[109],"it":[110],"could":[111],"detect":[112],"unseen":[113],"classes":[114],"when":[115],"testing.":[116],"second":[118],"designed":[128,153],"classify":[130],"detected":[132],"objects.":[133],"Images":[134],"were":[135,152],"preprocessed":[136],"before":[137],"input":[138],"remove":[146],"redundant":[147],"information.":[148],"Finally,":[149],"end-to-end":[150],"experiments":[151,169],"on":[154],"ImageNet":[156],"LOC":[157],"dataset.":[158],"Our":[159],"reached":[161],"high":[163],"mAP":[164],"80.76%":[166],"5-way-10-shot":[168],"significantly":[171],"outperformed":[172],"benchmark":[174],"method.":[175]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
