{"id":"https://openalex.org/W3161341522","doi":"https://doi.org/10.1109/icassp39728.2021.9414480","title":"Cross-Modal Knowledge Distillation For Fine-Grained One-Shot Classification","display_name":"Cross-Modal Knowledge Distillation For Fine-Grained One-Shot Classification","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3161341522","doi":"https://doi.org/10.1109/icassp39728.2021.9414480","mag":"3161341522"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9414480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101554229","display_name":"Jiabao Zhao","orcid":"https://orcid.org/0000-0002-0691-5741"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiabao Zhao","raw_affiliation_strings":["ECNU","School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECNU","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100398281","display_name":"Xin Lin","orcid":"https://orcid.org/0000-0001-6913-4654"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Lin","raw_affiliation_strings":["ECNU","School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECNU","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032964730","display_name":"Yifan Yang","orcid":"https://orcid.org/0000-0001-9127-168X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yifan Yang","raw_affiliation_strings":["Transwarp Technology (Shanghai) Co., Ltd, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Transwarp Technology (Shanghai) Co., Ltd, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100704230","display_name":"Jing Yang","orcid":"https://orcid.org/0000-0002-6407-1276"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Yang","raw_affiliation_strings":["School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010540039","display_name":"Liang He","orcid":"https://orcid.org/0000-0002-4723-5486"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang He","raw_affiliation_strings":["ECNU","School of Computer Science and Technology, East China Normal University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECNU","institution_ids":[]},{"raw_affiliation_string":"School of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"97","issue":null,"first_page":"4295","last_page":"4299"},"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":0.9997000098228455,"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":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9973000288009644,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9377999901771545,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8005586266517639},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.638699471950531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6159651279449463},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.5228272676467896},{"id":"https://openalex.org/keywords/knowledge-transfer","display_name":"Knowledge transfer","score":0.4961627423763275},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48156479001045227},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46934211254119873},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4603196978569031},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.4528816342353821},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.4432584345340729},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.4429146349430084},{"id":"https://openalex.org/keywords/domain-knowledge","display_name":"Domain knowledge","score":0.41473981738090515},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3558717370033264},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3390105962753296}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8005586266517639},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.638699471950531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6159651279449463},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.5228272676467896},{"id":"https://openalex.org/C2776960227","wikidata":"https://www.wikidata.org/wiki/Q2586354","display_name":"Knowledge transfer","level":2,"score":0.4961627423763275},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48156479001045227},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46934211254119873},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4603196978569031},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.4528816342353821},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.4432584345340729},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.4429146349430084},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.41473981738090515},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3558717370033264},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3390105962753296},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"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/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C56739046","wikidata":"https://www.wikidata.org/wiki/Q192060","display_name":"Knowledge management","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp39728.2021.9414480","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9414480","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321885","display_name":"Science and Technology Commission of Shanghai Municipality","ror":"https://ror.org/03kt66j61"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1690739335","https://openalex.org/W1797268635","https://openalex.org/W1821462560","https://openalex.org/W1898560071","https://openalex.org/W2032699694","https://openalex.org/W2042437279","https://openalex.org/W2398118205","https://openalex.org/W2471768434","https://openalex.org/W2601450892","https://openalex.org/W2604763608","https://openalex.org/W2737725206","https://openalex.org/W2753160622","https://openalex.org/W2763070548","https://openalex.org/W2798836702","https://openalex.org/W2799062425","https://openalex.org/W2892122929","https://openalex.org/W2894906112","https://openalex.org/W2949602577","https://openalex.org/W2963078860","https://openalex.org/W2963341924","https://openalex.org/W2963845150","https://openalex.org/W2964078140","https://openalex.org/W2964118293","https://openalex.org/W2970689606","https://openalex.org/W2971047694","https://openalex.org/W2985128858","https://openalex.org/W2997336365","https://openalex.org/W3035370595","https://openalex.org/W3099486271","https://openalex.org/W4288593364","https://openalex.org/W4289382675","https://openalex.org/W4300514939","https://openalex.org/W6637551013","https://openalex.org/W6638319203","https://openalex.org/W6638523607","https://openalex.org/W6717697761","https://openalex.org/W6735236233","https://openalex.org/W6736057607","https://openalex.org/W6743661861","https://openalex.org/W6751959828","https://openalex.org/W6754673040","https://openalex.org/W6755318597","https://openalex.org/W6758314753","https://openalex.org/W6766966499"],"related_works":["https://openalex.org/W2074502265","https://openalex.org/W4214877189","https://openalex.org/W2773965352","https://openalex.org/W2381179799","https://openalex.org/W2980279061","https://openalex.org/W2334685461","https://openalex.org/W2366718574","https://openalex.org/W2359774528","https://openalex.org/W4298312966","https://openalex.org/W2325697621"],"abstract_inverted_index":{"Few-shot":[0],"learning":[1],"can":[2,89,155],"recognize":[3],"a":[4,10,19,42,66,108,113,126,181],"novel":[5],"category":[6],"based":[7,124],"on":[8,125,150],"only":[9,123],"few":[11,127],"samples":[12,23,106,128],"because":[13],"it":[14,37,179],"learns":[15],"to":[16,40,56,72,84,143],"learn":[17],"from":[18],"lot":[20],"of":[21,60,104,159,172],"labeled":[22],"during":[24],"the":[25,32,58,79,91,101,105,118,134,170,173],"training":[26,112],"process.":[27],"When":[28],"data":[29],"is":[30,34,38,180],"insufficient,":[31],"performance":[33],"affected.":[35],"And":[36],"expensive":[39],"obtain":[41],"large-scale":[43],"finegrained":[44],"dataset":[45],"with":[46],"annotation.":[47],"In":[48],"this":[49],"paper,":[50],"we":[51],"adopt":[52],"domain-":[53],"specific":[54],"knowledge":[55,68,132,161],"fill":[57],"gap":[59,93],"insufficient":[61],"annotated":[62],"data.":[63],"We":[64],"propose":[65,78],"cross-modal":[67,86,160],"distillation":[69],"(CMKD)":[70],"framework":[71,138],"do":[73],"fine-grained":[74],"one-shot":[75],"classification":[76],"and":[77,164],"Spatial":[80],"Relation":[81],"Loss":[82],"(SRL)":[83],"transfer":[85],"information,":[87],"which":[88],"tackle":[90],"semantic":[92],"between":[94],"multimodal":[95],"features.":[96],"The":[97],"teacher":[98],"network":[99,120],"distills":[100],"spatial":[102],"relationship":[103],"as":[107],"soft":[109],"target":[110],"for":[111],"unimodal":[114],"student":[115,119,174,183],"network.":[116,184],"Notably,":[117],"makes":[121],"predictions":[122],"without":[129],"any":[130],"external":[131],"in":[133,162],"application.":[135],"This":[136],"model-agnostic":[137],"will":[139],"be":[140],"well":[141],"adapted":[142],"other":[144],"few-shot":[145,166],"models.":[146],"Extensive":[147],"experimental":[148],"results":[149],"benchmarks":[151],"demonstrate":[152],"that":[153],"CMKD":[154],"make":[156],"full":[157],"use":[158],"image":[163],"text":[165],"classification.":[167],"CKMD":[168],"improves":[169],"performances":[171],"networks":[175],"significantly,":[176],"even":[177],"if":[178],"state-of-the-art":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}