{"id":"https://openalex.org/W7127566564","doi":"https://doi.org/10.3390/e28020180","title":"Learnable Feature Disentanglement with Temporal-Complemented Motion Enhancement for Micro-Expression Recognition","display_name":"Learnable Feature Disentanglement with Temporal-Complemented Motion Enhancement for Micro-Expression Recognition","publication_year":2026,"publication_date":"2026-02-04","ids":{"openalex":"https://openalex.org/W7127566564","doi":"https://doi.org/10.3390/e28020180","pmid":"https://pubmed.ncbi.nlm.nih.gov/41751683"},"language":"en","primary_location":{"id":"doi:10.3390/e28020180","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28020180","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/e28020180","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Yu Qian","orcid":"https://orcid.org/0009-0003-4638-6287"},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Qian","raw_affiliation_strings":["School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, China"],"raw_orcid":"https://orcid.org/0009-0003-4638-6287","affiliations":[{"raw_affiliation_string":"School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Shucheng Huang","orcid":"https://orcid.org/0000-0002-5435-5961"},"institutions":[{"id":"https://openalex.org/I4210096899","display_name":"Jiangsu University of Science and Technology","ror":"https://ror.org/00tyjp878","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210096899"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shucheng Huang","raw_affiliation_strings":["School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, China"],"raw_orcid":"https://orcid.org/0000-0002-5435-5961","affiliations":[{"raw_affiliation_string":"School of Computer, Jiangsu University of Science and Technology, Zhenjiang 212100, China","institution_ids":["https://openalex.org/I4210096899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053430305","display_name":"Kai Qu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162215","display_name":"Naval Aeronautical and Astronautical University","ror":"https://ror.org/02j2yhq26","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210162215"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Qu","raw_affiliation_strings":["College of Naval Coast Defense Army, Navy Aviation University, Yantai 264000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Naval Coast Defense Army, Navy Aviation University, Yantai 264000, China","institution_ids":["https://openalex.org/I4210162215"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210096899"],"apc_list":{"value":2000,"currency":"CHF","value_usd":2165},"apc_paid":{"value":2000,"currency":"CHF","value_usd":2165},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16492255,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"2","first_page":"180","last_page":"180"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9251000285148621,"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":0.9251000285148621,"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/T11448","display_name":"Face recognition and analysis","score":0.023099999874830246,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.008899999782443047,"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/discriminative-model","display_name":"Discriminative model","score":0.6496000289916992},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6104999780654907},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6079000234603882},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5936999917030334},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5705999732017517},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5562000274658203},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5128999948501587},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.42010000348091125},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.414000004529953}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6890000104904175},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6759999990463257},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6496000289916992},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6104999780654907},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6079000234603882},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5936999917030334},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5705999732017517},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5562000274658203},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5128999948501587},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.42010000348091125},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4065000116825104},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.3801000118255615},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36079999804496765},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C145912823","wikidata":"https://www.wikidata.org/wiki/Q113558","display_name":"Dynamics (music)","level":2,"score":0.3424000144004822},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.33480000495910645},{"id":"https://openalex.org/C2777749129","wikidata":"https://www.wikidata.org/wiki/Q17148469","display_name":"Robust principal component analysis","level":3,"score":0.3310999870300293},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.32199999690055847},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.321399986743927},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.31299999356269836},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.30649998784065247},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C51432778","wikidata":"https://www.wikidata.org/wiki/Q1259145","display_name":"Independent component analysis","level":2,"score":0.29739999771118164},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.296099990606308},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C193415008","wikidata":"https://www.wikidata.org/wiki/Q639681","display_name":"Network architecture","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3390/e28020180","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28020180","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},{"id":"pmid:41751683","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/41751683","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":"Entropy (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:doaj.org/article:754030d0c3c641728bb988a40505ad0f","is_oa":false,"landing_page_url":"https://doaj.org/article/754030d0c3c641728bb988a40505ad0f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy, Vol 28, Iss 2, p 180 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:12939205","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC12939205/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Entropy (Basel)","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/e28020180","is_oa":true,"landing_page_url":"https://doi.org/10.3390/e28020180","pdf_url":null,"source":{"id":"https://openalex.org/S195231649","display_name":"Entropy","issn_l":"1099-4300","issn":["1099-4300"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Entropy","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7820599675178528,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G6396449109","display_name":null,"funder_award_id":"62276118","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":42,"referenced_works":["https://openalex.org/W565148957","https://openalex.org/W1854318472","https://openalex.org/W2019111214","https://openalex.org/W2093033615","https://openalex.org/W2163352848","https://openalex.org/W2237362194","https://openalex.org/W2263218431","https://openalex.org/W2399188776","https://openalex.org/W2478411578","https://openalex.org/W2526853616","https://openalex.org/W2623355927","https://openalex.org/W2737463186","https://openalex.org/W2911617386","https://openalex.org/W2959679536","https://openalex.org/W2962162344","https://openalex.org/W2962858109","https://openalex.org/W3012119275","https://openalex.org/W3045994539","https://openalex.org/W3080756971","https://openalex.org/W3101257721","https://openalex.org/W3124823188","https://openalex.org/W3129176834","https://openalex.org/W3139546544","https://openalex.org/W3182710365","https://openalex.org/W3195543922","https://openalex.org/W3206283519","https://openalex.org/W4200366598","https://openalex.org/W4206426170","https://openalex.org/W4224951303","https://openalex.org/W4296050207","https://openalex.org/W4312399808","https://openalex.org/W4386047789","https://openalex.org/W4386075510","https://openalex.org/W4389611070","https://openalex.org/W4400911572","https://openalex.org/W4401246682","https://openalex.org/W4405315888","https://openalex.org/W4408245045","https://openalex.org/W4408542742","https://openalex.org/W4408706994","https://openalex.org/W4413146579","https://openalex.org/W4416250747"],"related_works":[],"abstract_inverted_index":{"Micro-expressions":[0],"(MEs)":[1],"are":[2,73,100],"involuntary":[3],"facial":[4,91,96,184],"movements":[5],"that":[6,95,125,206],"reveal":[7],"genuine":[8],"emotions,":[9],"holding":[10],"significant":[11],"value":[12],"in":[13],"fields":[14],"like":[15],"deception":[16],"detection":[17],"and":[18,54,60,72,98,148,202,221],"psychological":[19],"diagnosis.":[20],"However,":[21,63],"micro-expression":[22],"recognition":[23],"(MER)":[24],"is":[25,135],"fundamentally":[26],"challenged":[27],"by":[28,86,138],"the":[29,80,87,108,152,167,173,193,214,217],"entanglement":[30],"of":[31,83,90,169,196,216],"subtle":[32,69,183],"emotional":[33,70],"motions":[34],"with":[35],"identity-specific":[36],"features.":[37,84],"Traditional":[38],"methods,":[39],"such":[40],"as":[41],"those":[42],"based":[43],"on":[44,200],"Robust":[45],"Principal":[46],"Component":[47],"Analysis":[48],"(RPCA),":[49],"attempt":[50],"to":[51,190],"separate":[52],"identity":[53,97],"motion":[55,161,181],"components":[56],"through":[57],"fixed":[58],"preprocessing":[59],"coarse":[61],"decomposition.":[62],"these":[64],"methods":[65],"can":[66],"inadvertently":[67],"remove":[68],"cues":[71],"disconnected":[74],"from":[75,163],"subsequent":[76],"module":[77,157,178],"training,":[78],"limiting":[79],"discriminative":[81],"power":[82],"Inspired":[85],"Bruce\u2013Young":[88],"model":[89,192],"cognition,":[92],"which":[93],"suggests":[94],"expression":[99],"processed":[101],"via":[102],"independent":[103],"neural":[104],"routes,":[105],"we":[106],"recognize":[107],"need":[109],"for":[110,117],"a":[111,122,139],"more":[112],"dynamic,":[113],"learnable":[114,129,219],"disentanglement":[115,131,220],"paradigm":[116],"MER.":[118],"We":[119],"propose":[120],"LFD-TCMEN,":[121],"novel":[123],"network":[124,134],"introduces":[126],"an":[127],"end-to-end":[128],"feature":[130],"framework.":[132],"The":[133],"synergistically":[136],"optimized":[137],"multi-task":[140],"objective":[141],"unifying":[142],"orthogonality,":[143],"reconstruction,":[144],"consistency,":[145],"cycle,":[146],"identity,":[147],"classification":[149],"losses.":[150],"Specifically,":[151],"Disentangle":[153],"Representation":[154],"Learning":[155],"(DRL)":[156],"adaptively":[158],"isolates":[159],"pure":[160],"patterns":[162],"subject-specific":[164],"appearance,":[165],"overcoming":[166],"limitations":[168],"static":[170],"preprocessing,":[171],"while":[172],"Temporal-Complemented":[174],"Motion":[175],"Enhancement":[176],"(TCME)":[177],"integrates":[179],"purified":[180],"representations\u2014highlighting":[182],"muscle":[185],"activations\u2014with":[186],"optical":[187],"flow":[188],"dynamics":[189],"comprehensively":[191],"spatiotemporal":[194],"evolution":[195],"MEs.":[197],"Extensive":[198],"experiments":[199],"CAS(ME)3":[201],"DFME":[203],"benchmarks":[204],"demonstrate":[205],"our":[207],"method":[208],"achieves":[209],"state-of-the-art":[210],"cross-subject":[211],"performance,":[212],"validating":[213],"efficacy":[215],"proposed":[218],"synergistic":[222],"optimization.":[223]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-06T00:00:00"}
