{"id":"https://openalex.org/W4388854781","doi":"https://doi.org/10.1109/tnnls.2023.3331648","title":"Proposal Distribution Calibration for Few-Shot Object Detection","display_name":"Proposal Distribution Calibration for Few-Shot Object Detection","publication_year":2023,"publication_date":"2023-11-21","ids":{"openalex":"https://openalex.org/W4388854781","doi":"https://doi.org/10.1109/tnnls.2023.3331648","pmid":"https://pubmed.ncbi.nlm.nih.gov/37988202"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2023.3331648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3331648","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5102004554","display_name":"Bohao Li","orcid":"https://orcid.org/0000-0001-7354-2116"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bohao Li","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100633842","display_name":"Chang Liu","orcid":"https://orcid.org/0000-0001-6747-0646"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chang Liu","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083561202","display_name":"Mengnan Shi","orcid":"https://orcid.org/0009-0001-2648-0765"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengnan Shi","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032868375","display_name":"Xiaozhong Chen","orcid":"https://orcid.org/0000-0003-1306-601X"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaozhong Chen","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024401174","display_name":"Xiangyang Ji","orcid":"https://orcid.org/0000-0002-7333-9975"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangyang Ji","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015317495","display_name":"Qixiang Ye","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qixiang Ye","raw_affiliation_strings":["School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102004554"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":1.5711,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86743869,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"36","issue":"1","first_page":"1911","last_page":"1918"},"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":0.9991999864578247,"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":0.9991999864578247,"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":0.9991000294685364,"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":0.9897000193595886,"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/pascal","display_name":"Pascal (unit)","score":0.7386640906333923},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7268902659416199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5254765748977661},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5010077953338623},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.48473379015922546},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4678172767162323},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.46270158886909485},{"id":"https://openalex.org/keywords/base","display_name":"Base (topology)","score":0.4414578378200531},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.44056373834609985},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43069469928741455},{"id":"https://openalex.org/keywords/region-of-interest","display_name":"Region of interest","score":0.4223012924194336},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.4212932586669922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38620808720588684},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36856019496917725},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14386975765228271},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13101178407669067}],"concepts":[{"id":"https://openalex.org/C75608658","wikidata":"https://www.wikidata.org/wiki/Q44395","display_name":"Pascal (unit)","level":2,"score":0.7386640906333923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7268902659416199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5254765748977661},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5010077953338623},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.48473379015922546},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4678172767162323},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.46270158886909485},{"id":"https://openalex.org/C42058472","wikidata":"https://www.wikidata.org/wiki/Q810214","display_name":"Base (topology)","level":2,"score":0.4414578378200531},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.44056373834609985},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43069469928741455},{"id":"https://openalex.org/C19609008","wikidata":"https://www.wikidata.org/wiki/Q2138203","display_name":"Region of interest","level":2,"score":0.4223012924194336},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.4212932586669922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38620808720588684},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36856019496917725},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14386975765228271},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13101178407669067},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2023.3331648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2023.3331648","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Transactions on Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:37988202","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37988202","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1295000622","display_name":null,"funder_award_id":"61836012","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6113573069","display_name":null,"funder_award_id":"62171431","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6735075065","display_name":null,"funder_award_id":"62225208","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"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2031489346","https://openalex.org/W2037227137","https://openalex.org/W2418306335","https://openalex.org/W2519882289","https://openalex.org/W2735531870","https://openalex.org/W2912497862","https://openalex.org/W2962799101","https://openalex.org/W2963037989","https://openalex.org/W2963078860","https://openalex.org/W2963845150","https://openalex.org/W2964105864","https://openalex.org/W2983156430","https://openalex.org/W2996173702","https://openalex.org/W3009213340","https://openalex.org/W3012255272","https://openalex.org/W3024536663","https://openalex.org/W3047669212","https://openalex.org/W3093412994","https://openalex.org/W3096609285","https://openalex.org/W3097651496","https://openalex.org/W3108189450","https://openalex.org/W3120093105","https://openalex.org/W3131068231","https://openalex.org/W3138516171","https://openalex.org/W3160694286","https://openalex.org/W3164709496","https://openalex.org/W3166574225","https://openalex.org/W3168126734","https://openalex.org/W3169575272","https://openalex.org/W3169708801","https://openalex.org/W3171521713","https://openalex.org/W3174017448","https://openalex.org/W3174396556","https://openalex.org/W3175577495","https://openalex.org/W3180725527","https://openalex.org/W4213436958","https://openalex.org/W4214724741","https://openalex.org/W4226001826","https://openalex.org/W4289535682","https://openalex.org/W4292787476","https://openalex.org/W4295046681","https://openalex.org/W4312058481","https://openalex.org/W4312702383","https://openalex.org/W4312755049","https://openalex.org/W4313156423","https://openalex.org/W4366083832","https://openalex.org/W6717697761","https://openalex.org/W6736057607","https://openalex.org/W6743661861","https://openalex.org/W6774983715","https://openalex.org/W6776700526","https://openalex.org/W6779913302","https://openalex.org/W6788840927","https://openalex.org/W6803928784","https://openalex.org/W6860508179","https://openalex.org/W6929495744"],"related_works":["https://openalex.org/W4376620596","https://openalex.org/W3177249605","https://openalex.org/W2534152068","https://openalex.org/W4299545679","https://openalex.org/W3138508047","https://openalex.org/W1972515067","https://openalex.org/W1689909837","https://openalex.org/W4293054914","https://openalex.org/W4313315626","https://openalex.org/W2963418361"],"abstract_inverted_index":{"Adapting":[0],"object":[1,20],"detectors":[2],"learned":[3,65],"with":[4,49,195],"sufficient":[5],"supervision":[6],"to":[7,30,72,120,159,181],"novel":[8,77,104,182],"classes":[9],"under":[10],"low":[11],"data":[12,87],"regimes":[13],"is":[14,27,70,208],"charming":[15],"yet":[16,113],"challenging.":[17],"In":[18,106],"few-shot":[19],"detection":[21],"(FSOD),":[22],"the":[23,32,60,64,85,90,95,123,129,155,161,172,178,186,200],"two-step":[24],"training":[25,62,140],"paradigm":[26],"widely":[28],"adopted":[29],"mitigate":[31],"severe":[33],"sample":[34,151],"imbalance,":[35],"i.e.,":[36],"holistic":[37],"pre-training":[38],"on":[39,154,185],"base":[40,61,139,156,179],"classes,":[41],"then":[42],"partial":[43],"fine-tuning":[44],"in":[45,59,80,138],"a":[46,111],"balanced":[47],"setting":[48],"all":[50],"classes.":[51,105,183],"Since":[52],"unlabeled":[53],"instances":[54],"are":[55],"suppressed":[56],"as":[57],"backgrounds":[58],"phase,":[63],"region":[66,96],"proposal":[67,91,115,157],"network":[68],"(RPN)":[69],"prone":[71],"produce":[73],"biased":[74],"proposals":[75,152,174],"for":[76,146,175,205],"instances,":[78],"resulting":[79],"dramatic":[81],"performance":[82],"degradation.":[83],"Unfortunately,":[84],"extreme":[86],"scarcity":[88],"aggravates":[89],"distribution":[92,116,162],"bias,":[93],"hindering":[94],"of":[97,128,202],"interest":[98],"(RoI)":[99],"head":[100,131],"from":[101],"evolving":[102],"toward":[103],"this":[107],"brief,":[108],"we":[109,150],"introduce":[110],"simple":[112],"effective":[114],"calibration":[117],"(PDC)":[118],"approach":[119],"neatly":[121],"enhance":[122],"localization":[124,135,167],"and":[125,141,164,168,191],"classification":[126,169],"abilities":[127],"RoI":[130],"by":[132],"recycling":[133],"its":[134],"ability":[136],"endowed":[137],"enriching":[142],"high-quality":[143],"positive":[144],"samples":[145],"semantic":[147],"fine-tuning.":[148],"Specifically,":[149],"based":[153],"statistics":[158],"calibrate":[160],"bias":[163],"impose":[165],"additional":[166],"losses":[170],"upon":[171],"sampled":[173],"fast":[176],"expanding":[177],"detector":[180],"Experiments":[184],"commonly":[187],"used":[188],"Pascal":[189],"VOC":[190],"MS":[192],"COCO":[193],"datasets":[194],"explicit":[196],"state-of-the-art":[197],"performances":[198],"justify":[199],"efficacy":[201],"our":[203],"PDC":[204],"FSOD.":[206],"Code":[207],"available":[209],"at":[210],"github.com/Bohao-Lee/PDC.":[211]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}