{"id":"https://openalex.org/W4381429398","doi":"https://doi.org/10.1109/tpami.2023.3282971","title":"No Adversaries to Zero-Shot Learning: Distilling an Ensemble of Gaussian Feature Generators","display_name":"No Adversaries to Zero-Shot Learning: Distilling an Ensemble of Gaussian Feature Generators","publication_year":2023,"publication_date":"2023-06-20","ids":{"openalex":"https://openalex.org/W4381429398","doi":"https://doi.org/10.1109/tpami.2023.3282971","pmid":"https://pubmed.ncbi.nlm.nih.gov/37339038"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2023.3282971","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3282971","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10158446.pdf","source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10158446.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043110801","display_name":"Jacopo Cavazza","orcid":"https://orcid.org/0000-0002-4912-6961"},"institutions":[{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Jacopo Cavazza","raw_affiliation_strings":["Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, GE, Italy","Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","Visual Geometry and Modelling (VGM) Department, Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy"],"raw_orcid":"https://orcid.org/0000-0002-4912-6961","affiliations":[{"raw_affiliation_string":"Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"Visual Geometry and Modelling (VGM) Department, Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007242502","display_name":"Vittorio Murino","orcid":"https://orcid.org/0000-0002-8645-2328"},"institutions":[{"id":"https://openalex.org/I119439378","display_name":"University of Verona","ror":"https://ror.org/039bp8j42","country_code":"IT","type":"education","lineage":["https://openalex.org/I119439378"]},{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]},{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Vittorio Murino","raw_affiliation_strings":["Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, GE, Italy","DIBRIS, University of Genova, Italy","Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","Department of Computer Science, University of Verona, Italy"],"raw_orcid":"https://orcid.org/0000-0002-8645-2328","affiliations":[{"raw_affiliation_string":"Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"DIBRIS, University of Genova, Italy","institution_ids":["https://openalex.org/I83816512"]},{"raw_affiliation_string":"Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"Department of Computer Science, University of Verona, Italy","institution_ids":["https://openalex.org/I119439378"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046971342","display_name":"Alessio Del Bue","orcid":"https://orcid.org/0000-0002-2262-4872"},"institutions":[{"id":"https://openalex.org/I30771326","display_name":"Italian Institute of Technology","ror":"https://ror.org/042t93s57","country_code":"IT","type":"facility","lineage":["https://openalex.org/I30771326"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Alessio Del Bue","raw_affiliation_strings":["Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, GE, Italy","Visual Geometry and Modelling (VGM) Department, Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy"],"raw_orcid":"https://orcid.org/0000-0002-2262-4872","affiliations":[{"raw_affiliation_string":"Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"Visual Geometry and Modelling (VGM) Department, Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]},{"raw_affiliation_string":"Pattern Analysis and Computer Vision (PAVIS), Istituto Italiano di Tecnologia, Via Enrico Melen 83, Genova, GE, Italy","institution_ids":["https://openalex.org/I30771326"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.9369,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.92647262,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"45","issue":"10","first_page":"12167","last_page":"12178"},"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":0.9998999834060669,"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":0.9998999834060669,"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/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9789999723434448,"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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.91839998960495,"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/softmax-function","display_name":"Softmax function","score":0.763592541217804},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7392479777336121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6981520056724548},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5562773942947388},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5530732274055481},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5389851331710815},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.49759724736213684},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4485090672969818},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4446132779121399},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.42502880096435547},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.42316097021102905},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.256001353263855}],"concepts":[{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.763592541217804},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7392479777336121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6981520056724548},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5562773942947388},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5530732274055481},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5389851331710815},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.49759724736213684},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4485090672969818},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4446132779121399},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.42502880096435547},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.42316097021102905},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.256001353263855},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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":3,"locations":[{"id":"doi:10.1109/tpami.2023.3282971","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3282971","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10158446.pdf","source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},{"id":"pmid:37339038","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37339038","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 pattern analysis and machine intelligence","raw_type":null},{"id":"pmh:oai:iris.unige.it:11567/1237735","is_oa":false,"landing_page_url":"https://hdl.handle.net/11567/1237735","pdf_url":null,"source":{"id":"https://openalex.org/S4377196291","display_name":"CINECA IRIS Institutial Research Information System (University of Genoa)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I83816512","host_organization_name":"University of Genoa","host_organization_lineage":["https://openalex.org/I83816512"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1109/tpami.2023.3282971","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tpami.2023.3282971","pdf_url":"https://ieeexplore.ieee.org/ielx7/34/4359286/10158446.pdf","source":{"id":"https://openalex.org/S199944782","display_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","issn_l":"0162-8828","issn":["0162-8828","1939-3539","2160-9292"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Pattern Analysis and Machine Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4381429398.pdf","grobid_xml":"https://content.openalex.org/works/W4381429398.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W652269744","https://openalex.org/W1542713999","https://openalex.org/W1821462560","https://openalex.org/W2017814585","https://openalex.org/W2123024445","https://openalex.org/W2150856297","https://openalex.org/W2171061940","https://openalex.org/W2250646737","https://openalex.org/W2289084343","https://openalex.org/W2334493732","https://openalex.org/W2561940122","https://openalex.org/W2611632661","https://openalex.org/W2883124384","https://openalex.org/W2887567284","https://openalex.org/W2899867883","https://openalex.org/W2905548899","https://openalex.org/W2910472686","https://openalex.org/W2924476266","https://openalex.org/W2945291089","https://openalex.org/W2951574208","https://openalex.org/W2962689421","https://openalex.org/W2962716320","https://openalex.org/W2962762077","https://openalex.org/W2963283377","https://openalex.org/W2963499153","https://openalex.org/W2963545832","https://openalex.org/W2963846885","https://openalex.org/W2963960318","https://openalex.org/W2964162033","https://openalex.org/W2964307109","https://openalex.org/W2972244714","https://openalex.org/W2978762605","https://openalex.org/W2979571231","https://openalex.org/W2986692991","https://openalex.org/W2988205463","https://openalex.org/W2990947836","https://openalex.org/W2991813857","https://openalex.org/W2997886689","https://openalex.org/W2998708909","https://openalex.org/W3000538487","https://openalex.org/W3010805239","https://openalex.org/W3034379915","https://openalex.org/W3034730995","https://openalex.org/W3035297600","https://openalex.org/W3035655772","https://openalex.org/W3143107425","https://openalex.org/W6600609147","https://openalex.org/W6632702419","https://openalex.org/W6638523607","https://openalex.org/W6678470764","https://openalex.org/W6683305289","https://openalex.org/W6691430427","https://openalex.org/W6758059896","https://openalex.org/W6762466240","https://openalex.org/W6762840122"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3090555870","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W4382468411","https://openalex.org/W4318751837"],"abstract_inverted_index":{"In":[0,28],"zero-shot":[1],"learning":[2],"(ZSL),":[3],"the":[4,42,55,75,129,156,170],"task":[5],"of":[6,54,120,123,144,190],"recognizing":[7],"unseen":[8,96,161],"categories":[9],"when":[10],"no":[11],"data":[12],"for":[13,95,105],"training":[14],"is":[15,165],"available,":[16],"state-of-the-art":[17,198],"methods":[18],"generate":[19],"visual":[20,68],"features":[21,69],"from":[22,63],"semantic":[23],"auxiliary":[24],"information":[25],"(e.g.,":[26],"attributes).":[27],"this":[29],"work,":[30],"we":[31,117],"propose":[32,83],"a":[33,84,121,142,150,173],"valid":[34],"alternative":[35],"(simpler,":[36],"yet":[37],"better":[38,154],"scoring)":[39],"to":[40,57,74,88,127,140,153,168,197],"fulfill":[41],"very":[43],"same":[44],"task.":[45],"We":[46,82,135],"observe":[47],"that,":[48],"if":[49],"first-":[50,90],"and":[51,91,107,160],"second-order":[52,92],"statistics":[53],"classes":[56],"be":[58],"recognized":[59],"were":[60],"known,":[61],"sampling":[62],"Gaussian":[64,125,191],"distributions":[65,126],"would":[66],"synthesize":[67],"that":[70],"are":[71],"almost":[72],"identical":[73],"real":[76],"ones":[77],"as":[78],"per":[79],"classification":[80],"purposes.":[81],"novel":[85],"mathematical":[86],"framework":[87,99],"estimate":[89],"statistics,":[93,116],"even":[94],"classes:":[97],"our":[98],"builds":[100],"upon":[101],"prior":[102],"compatibility":[103],"functions":[104],"ZSL":[106],"does":[108],"not":[109],"require":[110],"additional":[111],"training.":[112],"Endowed":[113],"with":[114,195],"such":[115],"take":[118],"advantage":[119],"pool":[122,143],"class-specific":[124],"solve":[128],"feature":[130],"generation":[131],"stage":[132],"through":[133,180],"sampling.":[134],"exploit":[136],"an":[137],"ensemble":[138,171],"mechanism":[139],"aggregate":[141],"softmax":[145],"classifiers,":[146],"each":[147],"trained":[148],"in":[149],"one-seen-class-out":[151],"fashion":[152],"balance":[155],"performance":[157],"over":[158],"seen":[159],"classes.":[162],"Neural":[163],"distillation":[164],"finally":[166],"applied":[167],"fuse":[169],"into":[172],"single":[174],"architecture":[175],"which":[176],"can":[177],"perform":[178],"inference":[179],"one":[181],"forward":[182],"pass":[183],"only.":[184],"Our":[185],"method,":[186],"termed":[187],"Distilled":[188],"Ensemble":[189],"Generators,":[192],"scores":[193],"favorably":[194],"respect":[196],"works.":[199]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":10}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
