{"id":"https://openalex.org/W4415540474","doi":"https://doi.org/10.1145/3746027.3754775","title":"Sera: Separated Coarse-to-fine Representation Alignment for Cross-subject EEG-based Emotion Recognition","display_name":"Sera: Separated Coarse-to-fine Representation Alignment for Cross-subject EEG-based Emotion Recognition","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415540474","doi":"https://doi.org/10.1145/3746027.3754775"},"language":"en","primary_location":{"id":"doi:10.1145/3746027.3754775","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5027573356","display_name":"Zhihao Jia","orcid":"https://orcid.org/0000-0003-1941-9269"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhihao Jia","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Science, Beijing, China","Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]},{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103028387","display_name":"Meiyan Xu","orcid":"https://orcid.org/0000-0003-2838-9145"},"institutions":[{"id":"https://openalex.org/I9356336","display_name":"Minnan Normal University","ror":"https://ror.org/02vj1vm13","country_code":"CN","type":"education","lineage":["https://openalex.org/I9356336"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meiyan Xu","raw_affiliation_strings":["Minnan Normal University, Zhangzhou, China"],"affiliations":[{"raw_affiliation_string":"Minnan Normal University, Zhangzhou, China","institution_ids":["https://openalex.org/I9356336"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Jingyuan Wang","orcid":"https://orcid.org/0009-0002-8823-5578"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyuan Wang","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065497921","display_name":"Ziyu Jia","orcid":"https://orcid.org/0000-0002-8523-1419"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]},{"id":"https://openalex.org/I4210094879","display_name":"Shandong Institute of Automation","ror":"https://ror.org/00qdtba35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210094879","https://openalex.org/I4210142748"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ziyu Jia","raw_affiliation_strings":["Institute of Automation, Chinese Academy of Science, Beijing, China","Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Institute of Automation, Chinese Academy of Science, Beijing, China","institution_ids":["https://openalex.org/I4210094879"]},{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355406","display_name":"Yong Li","orcid":"https://orcid.org/0000-0002-6521-5921"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["School of Computer Science and Engineer, Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineer, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100424237","display_name":"Xinliang Zhou","orcid":"https://orcid.org/0000-0002-6392-6412"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xinliang Zhou","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101372238","display_name":"Chenyu Liu","orcid":"https://orcid.org/0009-0008-5634-6736"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chenyu Liu","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051198154","display_name":"Junfeng Yao","orcid":"https://orcid.org/0000-0002-2330-7406"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junfeng Yao","raw_affiliation_strings":["Xiamen University, Xiamen, China"],"affiliations":[{"raw_affiliation_string":"Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101401265","display_name":"Yi Ding","orcid":"https://orcid.org/0000-0003-2365-3568"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yi Ding","raw_affiliation_strings":["College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore"],"affiliations":[{"raw_affiliation_string":"College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore","institution_ids":["https://openalex.org/I172675005"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":9,"corresponding_author_ids":["https://openalex.org/A5027573356"],"corresponding_institution_ids":["https://openalex.org/I191208505","https://openalex.org/I4210094879"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30026026,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"5509","last_page":"5518"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/electroencephalography","display_name":"Electroencephalography","score":0.6450999975204468},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.603600025177002},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5873000025749207},{"id":"https://openalex.org/keywords/neurophysiology","display_name":"Neurophysiology","score":0.5320000052452087},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5120999813079834},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.492900013923645},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.47360000014305115},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.4009999930858612},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3646000027656555},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3610999882221222}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.734499990940094},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.6450999975204468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6373999714851379},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.603600025177002},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5873000025749207},{"id":"https://openalex.org/C152478114","wikidata":"https://www.wikidata.org/wiki/Q660910","display_name":"Neurophysiology","level":2,"score":0.5320000052452087},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5120999813079834},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.492900013923645},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.47360000014305115},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4318999946117401},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.4009999930858612},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3646000027656555},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3610999882221222},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.3531000018119812},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.35190001130104065},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.34769999980926514},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.3181000053882599},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.31459999084472656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3111000061035156},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.275299996137619},{"id":"https://openalex.org/C45273575","wikidata":"https://www.wikidata.org/wiki/Q578970","display_name":"Spectrogram","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2671000063419342},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.26350000500679016},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2556000053882599},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.25119999051094055}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3746027.3754775","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3746027.3754775","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:dr.ntu.edu.sg:10356/202556","is_oa":false,"landing_page_url":"https://hdl.handle.net/10356/202556","pdf_url":null,"source":{"id":"https://openalex.org/S4306402609","display_name":"DR-NTU (Nanyang Technological University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I172675005","host_organization_name":"Nanyang Technological University","host_organization_lineage":["https://openalex.org/I172675005"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":null,"raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5027233691","display_name":null,"funder_award_id":"No. 62072388","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":false,"pdf":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W2002055708","https://openalex.org/W2559463885","https://openalex.org/W2599124244","https://openalex.org/W2625929003","https://openalex.org/W2790404832","https://openalex.org/W2794345050","https://openalex.org/W2799657112","https://openalex.org/W2904296567","https://openalex.org/W2921773252","https://openalex.org/W2926366943","https://openalex.org/W2954192080","https://openalex.org/W2982126608","https://openalex.org/W3024961463","https://openalex.org/W3090425814","https://openalex.org/W3093125198","https://openalex.org/W3140416091","https://openalex.org/W3175715598","https://openalex.org/W3198867425","https://openalex.org/W3199638068","https://openalex.org/W4206634335","https://openalex.org/W4226548933","https://openalex.org/W4309675233","https://openalex.org/W4312597583","https://openalex.org/W4313036139","https://openalex.org/W4313367562","https://openalex.org/W4319934143","https://openalex.org/W4365443833","https://openalex.org/W4377293039","https://openalex.org/W4379233567","https://openalex.org/W4385483055","https://openalex.org/W4386973857","https://openalex.org/W4390971296","https://openalex.org/W4391097250","https://openalex.org/W4391774550","https://openalex.org/W4392309135","https://openalex.org/W4394002412","https://openalex.org/W4395028532","https://openalex.org/W4400975541","https://openalex.org/W4401025135","https://openalex.org/W4402773829","https://openalex.org/W4404522101","https://openalex.org/W4404576998","https://openalex.org/W4406921271"],"related_works":[],"abstract_inverted_index":{"Neuropsychology-inspired":[0],"models":[1],"have":[2],"been":[3],"utilized":[4],"in":[5,8,64],"recent":[6],"advances":[7],"EEG":[9,43,56,115,159],"emotion":[10,61,85],"recognition,":[11,62],"such":[12],"as":[13],"convolutional":[14],"networks":[15],"for":[16,21,60,83],"spatial":[17,35],"features":[18,33],"and":[19,34,92,125,179,184,191],"Transformers":[20],"temporal":[22,156],"dependencies.":[23],"While":[24],"these":[25],"methods":[26,169],"benefit":[27],"from":[28,173],"domain":[29,145],"knowledge":[30],"like":[31],"frequency-band":[32],"correlations,":[36],"most":[37],"overlook":[38],"the":[39,54,121,148,167,182],"fundamental":[40],"fact":[41],"that":[42,87,164],"signals":[44,57,116],"are":[45],"complex":[46],"mixtures":[47],"of":[48],"neural":[49,122],"source":[50,90],"activities":[51,91],"recorded":[52],"at":[53],"scalp.":[55],"presenting":[58],"challenges":[59],"particularly":[63],"cross-subject":[65],"scenarios":[66],"due":[67],"to":[68,113,133,154,175],"significant":[69],"inter-subject":[70],"variance.":[71],"Inspired":[72],"by":[73],"neurophysiological":[74,192],"principles,":[75],"we":[76],"propose":[77],"a":[78,103,127,144],"novel":[79],"framework,":[80],"named":[81],"Sera,":[82],"EEG-based":[84],"recognition":[86],"explicitly":[88],"separates":[89],"aligns":[93],"representations":[94],"across":[95],"subjects.":[96],"Sera":[97,165],"introduces":[98],"two":[99],"key":[100],"components:":[101],"(1)":[102],"variational":[104],"autoencoder":[105],"(VAE)":[106],"with":[107,143,170],"multiple":[108],"multi-stage":[109],"decoders":[110],"(M2VAE)":[111],"designed":[112],"disentangle":[114],"into":[117],"independent":[118],"sources,":[119],"mimicking":[120],"generation":[123],"process,":[124],"(2)":[126],"coarse-to-fine":[128],"representation":[129],"alignment":[130,139,150],"block":[131],"(CFRA)":[132],"mitigate":[134],"subject-to-subject":[135],"variability.":[136],"The":[137,194],"coarse":[138],"employs":[140],"adversarial":[141],"training":[142],"discriminator,":[146],"while":[147],"fine-grained":[149],"matches":[151],"covariance":[152],"matrices":[153],"capture":[155],"correlations":[157],"within":[158],"segments.":[160],"Extensive":[161],"experiments":[162],"demonstrate":[163],"outperforms":[166],"state-of-the-art":[168],"improvements":[171],"ranging":[172],"1%":[174],"5%,":[176],"averaging":[177],"3.14%":[178],"3.05%":[180],"on":[181],"DEAP":[183],"DREAMER":[185],"datasets,":[186],"respectively,":[187],"confirming":[188],"its":[189],"effectiveness":[190],"grounding.":[193],"code":[195],"is":[196],"available":[197],"at:":[198],"https://github.com/JZH98/Sera-code.":[199]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-25T00:00:00"}