{"id":"https://openalex.org/W4289716938","doi":"https://doi.org/10.1109/tpami.2022.3196044","title":"Key Point Sensitive Loss for Long-tailed Visual Recognition","display_name":"Key Point Sensitive Loss for Long-tailed Visual Recognition","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4289716938","doi":"https://doi.org/10.1109/tpami.2022.3196044","pmid":"https://pubmed.ncbi.nlm.nih.gov/35921338"},"language":"en","primary_location":{"id":"doi:10.1109/tpami.2022.3196044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3196044","pdf_url":null,"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":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":"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/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":["Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-9433-9683","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China","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":["Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7629-4648","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I141568987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061132699","display_name":"Zhikai Hu","orcid":"https://orcid.org/0000-0001-7278-9977"},"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":"Zhikai Hu","raw_affiliation_strings":["Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0000-0001-7278-9977","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China","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":3.1304,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.92501594,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"45","issue":"4","first_page":"1","last_page":"14"},"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":0.9994999766349792,"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":0.9994999766349792,"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9988999962806702,"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/generalization","display_name":"Generalization","score":0.7251757979393005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6768420934677124},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.605650782585144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5767233371734619},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5284217000007629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4967387318611145},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.48022112250328064},{"id":"https://openalex.org/keywords/contextual-image-classification","display_name":"Contextual image classification","score":0.4435432255268097},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4192984402179718},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33616867661476135},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.24343600869178772},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2226976454257965}],"concepts":[{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.7251757979393005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6768420934677124},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.605650782585144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5767233371734619},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5284217000007629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4967387318611145},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.48022112250328064},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.4435432255268097},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4192984402179718},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33616867661476135},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.24343600869178772},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2226976454257965},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D007858","descriptor_name":"Learning","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true}],"locations_count":2,"locations":[{"id":"doi:10.1109/tpami.2022.3196044","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tpami.2022.3196044","pdf_url":null,"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":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":"journal-article"},{"id":"pmid:35921338","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/35921338","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}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/1","display_name":"No poverty","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":77,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W2117539524","https://openalex.org/W2118978333","https://openalex.org/W2131427446","https://openalex.org/W2148143831","https://openalex.org/W2194775991","https://openalex.org/W2440599146","https://openalex.org/W2549139847","https://openalex.org/W2609575245","https://openalex.org/W2732026016","https://openalex.org/W2750672897","https://openalex.org/W2767106145","https://openalex.org/W2784163702","https://openalex.org/W2797791043","https://openalex.org/W2797977484","https://openalex.org/W2905236149","https://openalex.org/W2913592748","https://openalex.org/W2962712569","https://openalex.org/W2962898354","https://openalex.org/W2962933664","https://openalex.org/W2963212406","https://openalex.org/W2963351448","https://openalex.org/W2963466847","https://openalex.org/W2963691377","https://openalex.org/W2964050365","https://openalex.org/W2969985801","https://openalex.org/W2970084480","https://openalex.org/W2992308087","https://openalex.org/W2995197345","https://openalex.org/W2998508940","https://openalex.org/W3034601242","https://openalex.org/W3035054804","https://openalex.org/W3035552357","https://openalex.org/W3095707208","https://openalex.org/W3096121526","https://openalex.org/W3101227480","https://openalex.org/W3103152812","https://openalex.org/W3118608800","https://openalex.org/W3122855191","https://openalex.org/W3125815192","https://openalex.org/W3128945844","https://openalex.org/W3166228617","https://openalex.org/W3172971995","https://openalex.org/W3173611024","https://openalex.org/W3174366534","https://openalex.org/W3176474016","https://openalex.org/W3177357839","https://openalex.org/W3182635745","https://openalex.org/W3186180121","https://openalex.org/W3202087803","https://openalex.org/W3203170887","https://openalex.org/W4297798436","https://openalex.org/W4366352743","https://openalex.org/W6603460400","https://openalex.org/W6605860122","https://openalex.org/W6637373629","https://openalex.org/W6683823733","https://openalex.org/W6732696085","https://openalex.org/W6738534199","https://openalex.org/W6739622702","https://openalex.org/W6743186171","https://openalex.org/W6744066916","https://openalex.org/W6745136726","https://openalex.org/W6747218270","https://openalex.org/W6754597090","https://openalex.org/W6760184523","https://openalex.org/W6760201928","https://openalex.org/W6763430915","https://openalex.org/W6764733053","https://openalex.org/W6767312631","https://openalex.org/W6768920361","https://openalex.org/W6780793664","https://openalex.org/W6780957418","https://openalex.org/W6784097300","https://openalex.org/W6787972765","https://openalex.org/W6799536747","https://openalex.org/W6842019321"],"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/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W2120455979","https://openalex.org/W3022347918"],"abstract_inverted_index":{"For":[0],"long-tailed":[1,162],"distributed":[2],"data,":[3],"existing":[4],"classification":[5,60,156,175],"models":[6],"often":[7],"learn":[8],"overwhelmingly":[9],"on":[10,69,81,148,161],"the":[11,16,49,55,59,67,72,95,108,112,119,130,137,154,166,174,178],"head":[12,188],"classes":[13,121,150,182],"while":[14,183],"ignoring":[15],"tail":[17,70,82,120,131,149,181],"classes,":[18,71],"resulting":[19],"in":[20,34,37,63,180,187],"poor":[21],"generalization":[22,56],"capability.":[23],"To":[24],"address":[25],"this":[26,35],"problem,":[27],"we":[28,85],"thereby":[29],"propose":[30,86],"a":[31,39,87],"new":[32],"approach":[33],"paper,":[36],"which":[38,128],"key":[40,50],"point":[41],"sensitive":[42],"(KPS)":[43],"loss":[44,75,113],"is":[45,116,169],"presented":[46],"to":[47,53,65,93,133],"regularize":[48],"points":[51],"strongly":[52],"improve":[54,66,153],"performance":[57,68,186],"of":[58,97,107,111,171,177],"model.":[61],"Meanwhile,":[62],"order":[64],"proposed":[73,140,167],"KPS":[74],"also":[76],"assigns":[77],"relatively":[78],"large":[79],"margins":[80],"classes.":[83,189],"Furthermore,":[84],"gradient":[88,109],"adjustment":[89],"(GA)":[90],"optimization":[91],"strategy":[92,142],"re-balance":[94],"gradients":[96],"positive":[98],"and":[99,151],"negative":[100,124,146],"samples":[101],"for":[102],"each":[103],"class.":[104],"By":[105],"virtue":[106],"analysis":[110],"function,":[114],"it":[115],"found":[117],"that":[118,165],"always":[122],"receive":[123],"signals":[125,147],"during":[126],"training,":[127],"misleads":[129],"prediction":[132],"be":[134],"biased":[135],"towards":[136],"head.":[138],"The":[139],"GA":[141],"can":[143],"circumvent":[144],"excessive":[145],"further":[152],"overall":[155],"accuracy.":[157],"Extensive":[158],"experiments":[159],"conducted":[160],"benchmarks":[163],"show":[164],"method":[168],"capable":[170],"significantly":[172],"improving":[173],"accuracy":[176],"model":[179],"maintaining":[184],"competent":[185]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":7}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
