{"id":"https://openalex.org/W4414359825","doi":"https://doi.org/10.24963/ijcai.2025/472","title":"A Cross-Modal Densely Guided Knowledge Distillation Based on Modality Rebalancing Strategy for Enhanced Unimodal Emotion Recognition","display_name":"A Cross-Modal Densely Guided Knowledge Distillation Based on Modality Rebalancing Strategy for Enhanced Unimodal Emotion Recognition","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359825","doi":"https://doi.org/10.24963/ijcai.2025/472"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/472","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/472","pdf_url":"https://www.ijcai.org/proceedings/2025/0472.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2025/0472.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100653345","display_name":"Shuang Wu","orcid":"https://orcid.org/0000-0003-1913-8125"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Wu","raw_affiliation_strings":["South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069748637","display_name":"Heng Liang","orcid":"https://orcid.org/0000-0002-9100-6007"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Heng Liang","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100419830","display_name":"Yong Zhang","orcid":"https://orcid.org/0000-0002-9587-4039"},"institutions":[{"id":"https://openalex.org/I3018263800","display_name":"Huzhou Normal University","ror":"https://ror.org/04mvpxy20","country_code":"CN","type":"education","lineage":["https://openalex.org/I3018263800"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Zhang","raw_affiliation_strings":["Huzhou University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huzhou University","institution_ids":["https://openalex.org/I3018263800"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103083448","display_name":"Yanlin Chen","orcid":"https://orcid.org/0009-0004-9382-5788"},"institutions":[{"id":"https://openalex.org/I57206974","display_name":"New York University","ror":"https://ror.org/0190ak572","country_code":"US","type":"education","lineage":["https://openalex.org/I57206974"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanlin Chen","raw_affiliation_strings":["New York University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York University","institution_ids":["https://openalex.org/I57206974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065497921","display_name":"Ziyu Jia","orcid":"https://orcid.org/0000-0002-8523-1419"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Jia","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2444,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95053285,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"4236","last_page":"4244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.84579998254776,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.84579998254776,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.781499981880188},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.753000020980835},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.737500011920929},{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.45660001039505005},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.365200012922287},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3449999988079071},{"id":"https://openalex.org/keywords/bridge","display_name":"Bridge (graph theory)","score":0.31850001215934753}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.781499981880188},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.753000020980835},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.737500011920929},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7211999893188477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6055999994277954},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4934999942779541},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3449999988079071},{"id":"https://openalex.org/C100776233","wikidata":"https://www.wikidata.org/wiki/Q2532492","display_name":"Bridge (graph theory)","level":2,"score":0.31850001215934753},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.2856999933719635},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.2822999954223633},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.27399998903274536},{"id":"https://openalex.org/C207685749","wikidata":"https://www.wikidata.org/wiki/Q2088941","display_name":"Domain knowledge","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/472","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/472","pdf_url":"https://www.ijcai.org/proceedings/2025/0472.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2025/472","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/472","pdf_url":"https://www.ijcai.org/proceedings/2025/0472.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4468112264","display_name":null,"funder_award_id":"62306317","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4414359825.pdf","grobid_xml":"https://content.openalex.org/works/W4414359825.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multimodal":[0],"emotion":[1,60,186,193],"recognition":[2,194],"has":[3],"garnered":[4],"significant":[5],"attention":[6],"for":[7,59,192],"its":[8],"ability":[9],"to":[10,16,27,33,65,74,107,117,145,157,166],"integrate":[11,119],"data":[12,31],"from":[13],"multiple":[14],"modalities":[15,106],"enhance":[17,75],"performance.":[18],"However,":[19],"physiological":[20],"signals":[21],"like":[22],"electroencephalogram":[23],"are":[24],"more":[25],"challenging":[26],"acquire":[28],"than":[29],"visual":[30,86],"due":[32],"higher":[34],"collection":[35],"costs":[36],"and":[37,162],"complexity.":[38],"This":[39],"limits":[40],"the":[41,67,76,85,101,114,141,146,159,177],"practical":[42],"application":[43],"of":[44,69,78,104],"multimodal":[45,71,120,142],"networks.":[46],"To":[47],"address":[48],"this":[49,51],"issue,":[50],"paper":[52],"proposes":[53],"a":[54,70,79,93,127],"cross-modal":[55],"knowledge":[56,138,171],"distillation":[57],"framework":[58,63,179],"recognition.":[61],"The":[62],"aims":[64],"leverage":[66],"strengths":[68],"teacher":[72,115,143,154],"network":[73,82,116,144],"performance":[77],"unimodal":[80,147],"student":[81,148],"using":[83],"only":[84],"modality":[87,95,109],"as":[88],"input.":[89],"Specifically,":[90],"we":[91,125],"design":[92],"prototype-based":[94],"rebalancing":[96],"strategy,":[97],"which":[98,135],"dynamically":[99],"adjusts":[100],"convergence":[102],"rates":[103],"different":[105],"mitigate":[108],"imbalance":[110],"issue.":[111],"It":[112],"enables":[113],"better":[118],"information.":[121],"Building":[122],"upon":[123],"this,":[124],"develop":[126],"Cross-Modal":[128],"Densely":[129],"Guided":[130],"Knowledge":[131],"Distillation":[132],"(CDGKD)":[133],"method,":[134],"effectively":[136],"transfers":[137],"extracted":[139],"by":[140],"network.":[149],"Our":[150],"CDGKD":[151],"uses":[152],"multi-level":[153],"assistant":[155],"networks":[156],"bridge":[158],"teacher-student":[160],"gap":[161],"employs":[163],"dense":[164],"guidance":[165],"reduce":[167],"error":[168],"accumulation":[169],"during":[170],"transfer.":[172],"Experimental":[173],"results":[174],"demonstrate":[175],"that":[176],"proposed":[178],"outperforms":[180],"existing":[181],"methods":[182],"on":[183],"two":[184],"public":[185],"datasets,":[187],"providing":[188],"an":[189],"effective":[190],"solution":[191],"in":[195],"modality-constrained":[196],"scenarios.":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}
