{"id":"https://openalex.org/W4221148493","doi":"https://doi.org/10.48550/arxiv.2203.01386","title":"Exploring Hierarchical Graph Representation for Large-Scale Zero-Shot Image Classification","display_name":"Exploring Hierarchical Graph Representation for Large-Scale Zero-Shot Image Classification","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4221148493","doi":"https://doi.org/10.48550/arxiv.2203.01386"},"language":"en","primary_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2203.01386","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"type":"preprint","type_crossref":"posted-content","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/abs/2203.01386","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100765686","display_name":"Kai Yi","orcid":"https://orcid.org/0000-0003-0415-3584"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi, Kai","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020511969","display_name":"Xiaoqian Shen","orcid":"https://orcid.org/0000-0001-6284-520X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shen, Xiaoqian","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070721407","display_name":"Yunhao Gou","orcid":"https://orcid.org/0000-0002-1352-794X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gou, Yunhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5085089542","display_name":"Mohamed Elhoseiny","orcid":"https://orcid.org/0000-0001-9659-1551"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Elhoseiny, Mohamed","raw_affiliation_strings":[],"affiliations":[]}],"institution_assertions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":0,"max":60},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9991,"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":0.9991,"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":0.9965,"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":0.9751,"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/benchmark","display_name":"Benchmark (surveying)","score":0.66358316},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting","score":0.65991837},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6007162}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.66358316},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.65991837},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6007162},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5722571},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5592249},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5027039},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.44373977},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.379492},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1853677},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2203.01386","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},{"is_oa":false,"landing_page_url":"https://api.datacite.org/dois/10.48550/arxiv.2203.01386","pdf_url":null,"source":{"id":"https://openalex.org/S4393179698","display_name":"DataCite API","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210145204","host_organization_name":"DataCite","host_organization_lineage":["https://openalex.org/I4210145204"],"host_organization_lineage_names":["DataCite"],"type":"metadata"},"license":null,"license_id":null,"version":null}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2203.01386","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":["Cornell University"],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.75}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W4313640622","https://openalex.org/W4205463238","https://openalex.org/W3103844505","https://openalex.org/W3082059448","https://openalex.org/W259157601","https://openalex.org/W2153315159","https://openalex.org/W2125652721","https://openalex.org/W2116862786","https://openalex.org/W1540371141"],"abstract_inverted_index":{"The":[0],"main":[1],"question":[2],"we":[3],"address":[4],"in":[5,30,43,127],"this":[6,35],"paper":[7],"is":[8,46,125],"how":[9],"to":[10,23,48,58,113],"scale":[11],"up":[12],"visual":[13,51],"recognition":[14],"of":[15,25,27],"unseen":[16,60],"classes,":[17],"also":[18,131],"known":[19],"as":[20,29,82],"zero-shot":[21],"learning,":[22],"tens":[24],"thousands":[26],"categories":[28,41],"the":[31,77,108,114,118],"ImageNet-21K":[32,119],"benchmark.":[33,120],"At":[34],"scale,":[36],"especially":[37],"with":[38],"many":[39],"fine-grained":[40],"included":[42],"ImageNet-21K,":[44],"it":[45],"critical":[47],"learn":[49],"quality":[50],"semantic":[52],"representations":[53],"that":[54,88,123],"are":[55,151],"discriminative":[56],"enough":[57],"recognize":[59],"classes":[61],"and":[62,141,149],"distinguish":[63],"them":[64],"from":[65],"seen":[66],"ones.":[67],"We":[68,121,130],"propose":[69],"a":[70],"\\emph{H}ierarchical":[71],"\\emph{G}raphical":[72],"knowledge":[73],"\\emph{R}epresentation":[74],"framework":[75],"for":[76],"confidence-based":[78],"classification":[79],"method,":[80],"dubbed":[81],"HGR-Net.":[83],"Our":[84,100,147],"experimental":[85],"results":[86],"demonstrate":[87],"HGR-Net":[89,124],"can":[90],"grasp":[91],"class":[92],"inheritance":[93],"relations":[94],"by":[95,110],"utilizing":[96],"hierarchical":[97],"conceptual":[98],"knowledge.":[99],"method":[101,134],"significantly":[102],"outperformed":[103],"all":[104],"existing":[105],"techniques,":[106],"boosting":[107],"performance":[109],"7\\%":[111],"compared":[112],"runner-up":[115],"approach":[116],"on":[117,135],"show":[122],"learning-efficient":[126],"few-shot":[128],"scenarios.":[129],"analyzed":[132],"our":[133],"smaller":[136],"datasets":[137],"like":[138],"ImageNet-21K-P,":[139],"2-hops":[140],"3-hops,":[142],"demonstrating":[143],"its":[144],"generalization":[145],"ability.":[146],"benchmark":[148],"code":[150],"available":[152],"at":[153],"https://kaiyi.me/p/hgrnet.html.":[154]},"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W4221148493","counts_by_year":[],"updated_date":"2024-12-15T16:37:32.199580","created_date":"2022-04-03"}