{"id":"https://openalex.org/W7155075966","doi":"https://doi.org/10.48550/arxiv.2604.17899","title":"MEDN: Motion-Emotion Feature Decoupling Network for Micro-Expression Recognition","display_name":"MEDN: Motion-Emotion Feature Decoupling Network for Micro-Expression Recognition","publication_year":2026,"publication_date":"2026-04-20","ids":{"openalex":"https://openalex.org/W7155075966","doi":"https://doi.org/10.48550/arxiv.2604.17899"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.17899","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17899","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.17899","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134111375","display_name":"Chenxing Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Chenxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134194624","display_name":"Kun Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Kun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134171505","display_name":"Qiguang Miao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Miao, Qiguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134104951","display_name":"Ruyi Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Ruyi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134175876","display_name":"Quan Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Quan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134119685","display_name":"Zongkai Yang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Zongkai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"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":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9930999875068665,"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":0.9930999875068665,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.0020000000949949026,"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/T11094","display_name":"Face Recognition and Perception","score":0.0005000000237487257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/emotion-recognition","display_name":"Emotion recognition","score":0.5893999934196472},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5576000213623047},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46779999136924744},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.4514000117778778},{"id":"https://openalex.org/keywords/decoupling","display_name":"Decoupling (probability)","score":0.40720000863075256},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.40529999136924744},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38440001010894775},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.3824999928474426},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3359000086784363}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7300000190734863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.649399995803833},{"id":"https://openalex.org/C2777438025","wikidata":"https://www.wikidata.org/wiki/Q1339090","display_name":"Emotion recognition","level":2,"score":0.5893999934196472},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5576000213623047},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46779999136924744},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.4514000117778778},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4453999996185303},{"id":"https://openalex.org/C205606062","wikidata":"https://www.wikidata.org/wiki/Q5249645","display_name":"Decoupling (probability)","level":2,"score":0.40720000863075256},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38440001010894775},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.3287000060081482},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.3246999979019165},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3158000111579895},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.30880001187324524},{"id":"https://openalex.org/C171018156","wikidata":"https://www.wikidata.org/wiki/Q7370306","display_name":"Rotation formalisms in three dimensions","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.29649999737739563},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.2928999960422516},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2676999866962433},{"id":"https://openalex.org/C6438553","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Affective computing","level":2,"score":0.26409998536109924},{"id":"https://openalex.org/C2777036941","wikidata":"https://www.wikidata.org/wiki/Q6917771","display_name":"Motion analysis","level":2,"score":0.26109999418258667},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.26100000739097595},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.2558000087738037},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2540000081062317},{"id":"https://openalex.org/C206310091","wikidata":"https://www.wikidata.org/wiki/Q750859","display_name":"Emotion classification","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.17899","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17899","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.17899","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.17899","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.5518438220024109}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Unlike":[0],"macro-expression,":[1],"micro-expression":[2],"does":[3],"not":[4],"follow":[5],"a":[6,18,67,78,119,175],"strictly":[7],"consistent":[8],"mapping":[9],"rule":[10],"between":[11],"emotions":[12],"and":[13,85,102,150,166,169,182],"Action":[14],"Units":[15],"(AUs).":[16],"As":[17],"result,":[19],"some":[20],"micro-expressions":[21],"share":[22],"identical":[23],"AUs":[24],"yet":[25],"represent":[26],"completely":[27],"opposite":[28],"emotional":[29],"categories,":[30],"making":[31],"them":[32],"highly":[33],"visually":[34],"similar.":[35],"Existing":[36],"microexpression":[37],"recognition":[38,172,180],"(MER)":[39],"methods":[40],"mostly":[41],"rely":[42],"on":[43,156],"explicit":[44,99],"facial":[45],"motion":[46,84,90,100,109,149,165],"cues":[47],"(e.g.,":[48],"optical":[49],"flow,":[50],"frame":[51],"differences,":[52],"AU":[53],"features)":[54],"while":[55],"ignoring":[56],"implicit":[57,114],"emotion":[58,86,110,115,151,167],"information.":[59],"To":[60],"tackle":[61],"this":[62,64],"issue,":[63],"paper":[65],"presents":[66],"Motion":[68],"Emotion":[69,121],"Feature":[70],"Decoupling":[71],"Network":[72],"(MEDN)":[73],"for":[74,178],"MER.":[75],"We":[76],"design":[77],"dual-branch":[79],"framework":[80],"to":[81,97,107,129,146],"separately":[82],"extract":[83],"features.":[87],"In":[88],"the":[89,98],"branch,":[91],"an":[92],"AU-detection":[93],"task":[94],"restricts":[95],"features":[96,152,168],"domain,":[101],"orthogonal":[103],"loss":[104],"is":[105,143],"adopted":[106],"reduce":[108],"feature":[111],"coupling.":[112],"For":[113],"modeling,":[116],"we":[117],"propose":[118],"Sparse":[120],"Vision":[122],"Transformer":[123],"(SEVit)":[124],"that":[125,161],"sparsifies":[126],"spatial":[127],"tokens":[128],"highlight":[130],"local":[131],"temporal":[132],"variations":[133],"with":[134],"multi-scale":[135],"sparsity":[136],"rates.":[137],"A":[138],"Collaborative":[139],"Fusion":[140],"Module":[141],"(CoFM)":[142],"further":[144],"developed":[145],"fuse":[147],"disentangled":[148],"adaptively.":[153],"Extensive":[154],"experiments":[155],"three":[157],"benchmark":[158],"datasets":[159],"validate":[160],"MEDN":[162],"effectively":[163],"decouples":[164],"achieves":[170],"superior":[171],"performance,":[173],"offering":[174],"new":[176],"perspective":[177],"enhancing":[179],"accuracy":[181],"generalization.":[183]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-22T00:00:00"}