{"id":"https://openalex.org/W4293519074","doi":"https://doi.org/10.1109/icme52920.2022.9860003","title":"Feature-Balanced Loss for Long-Tailed Visual Recognition","display_name":"Feature-Balanced Loss for Long-Tailed Visual Recognition","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4293519074","doi":"https://doi.org/10.1109/icme52920.2022.9860003"},"language":"en","primary_location":{"id":"doi:10.1109/icme52920.2022.9860003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9860003","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2305.10772","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100730941","display_name":"Mengke Li","orcid":"https://orcid.org/0000-0002-9433-9683"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Mengke Li","raw_affiliation_strings":["Hong Kong Baptist University,Department of Computer Science,Hong Kong","Department of Computer Science, Hong Kong Baptist University, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University,Department of Computer Science,Hong Kong","institution_ids":["https://openalex.org/I141568987"]},{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038516431","display_name":"Yiu\u2010ming Cheung","orcid":"https://orcid.org/0000-0001-7629-4648"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yiu-Ming Cheung","raw_affiliation_strings":["Hong Kong Baptist University,Department of Computer Science,Hong Kong","Department of Computer Science, Hong Kong Baptist University, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University,Department of Computer Science,Hong Kong","institution_ids":["https://openalex.org/I141568987"]},{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007147042","display_name":"Juyong Jiang","orcid":"https://orcid.org/0000-0003-0835-9686"},"institutions":[{"id":"https://openalex.org/I141568987","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131","country_code":"HK","type":"education","lineage":["https://openalex.org/I141568987"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Juyong Jiang","raw_affiliation_strings":["Hong Kong Baptist University,Department of Computer Science,Hong Kong","Department of Computer Science, Hong Kong Baptist University, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong Baptist University,Department of Computer Science,Hong Kong","institution_ids":["https://openalex.org/I141568987"]},{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong","institution_ids":["https://openalex.org/I141568987"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I141568987"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9998000264167786,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9983000159263611,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7348589897155762},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6769407391548157},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5782305002212524},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5665586590766907},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5662223100662231},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5354639887809753},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44138777256011963},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4313294291496277},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42477989196777344},{"id":"https://openalex.org/keywords/norm","display_name":"Norm (philosophy)","score":0.4109882712364197},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16867712140083313}],"concepts":[{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7348589897155762},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6769407391548157},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5782305002212524},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5665586590766907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5662223100662231},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5354639887809753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44138777256011963},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4313294291496277},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42477989196777344},{"id":"https://openalex.org/C191795146","wikidata":"https://www.wikidata.org/wiki/Q3878446","display_name":"Norm (philosophy)","level":2,"score":0.4109882712364197},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16867712140083313},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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":2,"locations":[{"id":"doi:10.1109/icme52920.2022.9860003","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9860003","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2305.10772","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.10772","pdf_url":"https://arxiv.org/pdf/2305.10772","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2305.10772","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2305.10772","pdf_url":"https://arxiv.org/pdf/2305.10772","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":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.7900000214576721}],"awards":[{"id":"https://openalex.org/G1769591887","display_name":null,"funder_award_id":"N_HKBU214/21","funder_id":"https://openalex.org/F4320325622","funder_display_name":"Japanese Respiratory Society"},{"id":"https://openalex.org/G4436389382","display_name":null,"funder_award_id":"61672444","funder_id":"https://openalex.org/F4320320955","funder_display_name":"Hong Kong Baptist University"},{"id":"https://openalex.org/G4787607161","display_name":null,"funder_award_id":"RC-FNRA-IG/18-19/SCI/03","funder_id":"https://openalex.org/F4320320955","funder_display_name":"Hong Kong Baptist University"},{"id":"https://openalex.org/G5140599133","display_name":null,"funder_award_id":"12201321","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8492407749","display_name":null,"funder_award_id":"12201321","funder_id":"https://openalex.org/F4320306709","funder_display_name":"Glaucoma Research Foundation"},{"id":"https://openalex.org/G8811941144","display_name":"\u5927\u6570\u636e\u5e73\u53f0\u4e0b\u57fa\u4e8e\u591a\u5143\u975e\u5b8c\u5907\u4fe1\u606f\u7684\u56fe\u50cf\u68c0\u7d22\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61672444","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306709","display_name":"Glaucoma Research Foundation","ror":"https://ror.org/05ez53b31"},{"id":"https://openalex.org/F4320320955","display_name":"Hong Kong Baptist University","ror":"https://ror.org/0145fw131"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320325622","display_name":"Japanese Respiratory Society","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4293519074.pdf","grobid_xml":"https://content.openalex.org/works/W4293519074.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W2104933073","https://openalex.org/W2108598243","https://openalex.org/W2296073425","https://openalex.org/W2440599146","https://openalex.org/W2617274020","https://openalex.org/W2732026016","https://openalex.org/W2795282075","https://openalex.org/W2797977484","https://openalex.org/W2884561390","https://openalex.org/W2962933664","https://openalex.org/W2963691377","https://openalex.org/W2964050365","https://openalex.org/W2970941190","https://openalex.org/W2995197345","https://openalex.org/W3034601242","https://openalex.org/W3035552357","https://openalex.org/W3042496707","https://openalex.org/W3118608800","https://openalex.org/W3122855191","https://openalex.org/W3166596953","https://openalex.org/W3177200443","https://openalex.org/W6637831805","https://openalex.org/W6675634716","https://openalex.org/W6738653663","https://openalex.org/W6750523955","https://openalex.org/W6764733053","https://openalex.org/W6768920361","https://openalex.org/W6787972765","https://openalex.org/W6792870994"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W4309346246","https://openalex.org/W2786094008","https://openalex.org/W3131501806","https://openalex.org/W2799683370","https://openalex.org/W2807745940"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"frequently":[3],"suffer":[4],"from":[5,41,69],"performance":[6,117,137],"degradation":[7],"when":[8],"the":[9,19,51,57,66,75,94,101,108,111,116,119,132,141],"training":[10],"data":[11,42],"is":[12,97],"long-tailed":[13,67,127],"because":[14],"several":[15],"majority":[16],"classes":[17,86],"dominate":[18],"training,":[20],"resulting":[21],"in":[22,33,100],"a":[23,30],"biased":[24],"model.":[25],"Recent":[26],"studies":[27],"have":[28],"made":[29],"great":[31],"effort":[32],"solving":[34],"this":[35,61],"issue":[36],"by":[37,87],"obtaining":[38],"good":[39],"representations":[40],"space,":[43],"but":[44],"few":[45],"of":[46,53,84,103,110,118],"them":[47,89],"pay":[48],"attention":[49],"to":[50],"influence":[52],"feature":[54,70,82],"norm":[55],"on":[56,124],"predicted":[58],"results.":[59],"In":[60],"paper,":[62],"we":[63,79],"therefore":[64],"address":[65],"problem":[68],"space":[71],"and":[72],"thereby":[73],"propose":[74],"feature-balanced":[76,133],"loss.":[77],"Specifically,":[78],"encourage":[80],"larger":[81],"norms":[83],"tail":[85,112],"giving":[88],"relatively":[90],"stronger":[91],"stimuli.":[92],"Moreover,":[93],"stimuli":[95],"intensity":[96],"gradually":[98],"increased":[99],"way":[102],"curriculum":[104],"learning,":[105],"which":[106],"improves":[107],"generalization":[109],"classes,":[113],"meanwhile":[114],"maintaining":[115],"head":[120],"classes.":[121],"Extensive":[122],"experiments":[123],"multiple":[125],"popular":[126],"recognition":[128],"benchmarks":[129],"demonstrate":[130],"that":[131],"loss":[134],"achieves":[135],"superior":[136],"gains":[138],"compared":[139],"with":[140],"state-of-the-art":[142],"methods.":[143]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}