{"id":"https://openalex.org/W7154201428","doi":"https://doi.org/10.48550/arxiv.2604.10541","title":"Bidirectional Learning of Facial Action Units and Expressions via Structured Semantic Mapping across Heterogeneous Datasets","display_name":"Bidirectional Learning of Facial Action Units and Expressions via Structured Semantic Mapping across Heterogeneous Datasets","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7154201428","doi":"https://doi.org/10.48550/arxiv.2604.10541"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.10541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10541","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2604.10541","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133576814","display_name":"Jia Li","orcid":"https://orcid.org/0009-0002-1169-4346"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Jia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133625966","display_name":"Yu Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133615499","display_name":"Yin Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Yin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040235604","display_name":"Zhenzhen Hu","orcid":"https://orcid.org/0000-0003-1042-8361"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Zhenzhen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133553278","display_name":"Yong Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Yong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133574243","display_name":"Richang Hong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong, Richang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133591285","display_name":"Shiguang Shan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shan, Shiguang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5100693187","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0001-6555-5558"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Meng","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":0.9860000014305115,"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":0.9860000014305115,"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":0.004000000189989805,"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":0.002199999988079071,"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/semantic-mapping","display_name":"Semantic mapping","score":0.5770999789237976},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5232999920845032},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.48030000925064087},{"id":"https://openalex.org/keywords/semantic-integration","display_name":"Semantic integration","score":0.4618000090122223},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.4438000023365021},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4237000048160553},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4221999943256378},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.4083000123500824},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.3986000120639801},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.3869999945163727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.815500020980835},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.5770999789237976},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5655999779701233},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5232999920845032},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4941999912261963},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.48030000925064087},{"id":"https://openalex.org/C110903229","wikidata":"https://www.wikidata.org/wiki/Q7449064","display_name":"Semantic integration","level":4,"score":0.4618000090122223},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4438000023365021},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4237000048160553},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4221999943256378},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4083000123500824},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.3986000120639801},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.3869999945163727},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.384799987077713},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.35089999437332153},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.349700003862381},{"id":"https://openalex.org/C197914299","wikidata":"https://www.wikidata.org/wiki/Q18650","display_name":"Semantic memory","level":3,"score":0.3424000144004822},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.33000001311302185},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.32829999923706055},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30820000171661377},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2957000136375427},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.28760001063346863},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2809999883174896},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26649999618530273},{"id":"https://openalex.org/C511149849","wikidata":"https://www.wikidata.org/wiki/Q7449051","display_name":"Semantic computing","level":3,"score":0.2655999958515167},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25699999928474426},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2565999925136566},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2540000081062317}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.10541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10541","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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.2604.10541","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.10541","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Facial":[0,182],"action":[1],"unit":[2],"(AU)":[3],"detection":[4,208],"and":[5,23,64,76,79,105,127,158,167,186,199,209,223],"facial":[6,16,122],"expression":[7,227],"(FE)":[8],"recognition":[9,211],"can":[10,229],"be":[11],"jointly":[12],"viewed":[13],"as":[14,155],"affective":[15,26],"behavior":[17],"tasks,":[18],"representing":[19],"fine-grained":[20,233],"muscular":[21],"activations":[22],"coarse-grained":[24],"holistic":[25,226],"states,":[27],"respectively.":[28],"Despite":[29],"their":[30],"inherent":[31],"semantic":[32,131,143,165],"correlation,":[33],"existing":[34],"studies":[35],"predominantly":[36],"focus":[37],"on":[38,205,219],"knowledge":[39,178,201],"transfer":[40],"from":[41,124,145,180],"AUs":[42],"to":[43],"FEs,":[44],"while":[45],"bidirectional":[46,98,200],"learning":[47,100,235],"remains":[48],"insufficiently":[49],"explored.":[50],"In":[51],"practice,":[52],"this":[53],"challenge":[54],"is":[55],"further":[56],"compounded":[57],"by":[58],"heterogeneous":[59,106,238],"data":[60,77,103],"conditions,":[61],"where":[62],"AU":[63,126,207,234],"FE":[65,128,210],"datasets":[66],"differ":[67],"in":[68,162,192,230],"annotation":[69],"paradigms":[70],"(frame-level":[71],"vs.\\":[72],"clip-level),":[73],"label":[74],"granularity,":[75],"availability":[78],"diversity,":[80],"hindering":[81],"effective":[82],"joint":[83],"learning.":[84],"To":[85],"address":[86],"these":[87],"issues,":[88],"we":[89],"propose":[90],"a":[91,115,134,163,169,188,193],"Structured":[92],"Semantic":[93,136],"Mapping":[94,172],"(SSM)":[95],"framework":[96],"for":[97],"AU--FE":[99],"under":[101],"different":[102],"domains":[104],"supervision.":[107],"SSM":[108,215],"consists":[109],"of":[110],"three":[111],"key":[112],"components:":[113],"(1)":[114],"shared":[116,164],"visual":[117],"backbone":[118],"that":[119,175,214,225],"learns":[120,187],"unified":[121],"representations":[123],"dynamic":[125],"videos;":[129],"(2)":[130],"mediation":[132],"via":[133],"Textual":[135],"Prototype":[137],"(TSP)":[138],"module,":[139],"which":[140],"constructs":[141],"structured":[142],"prototypes":[144],"fixed":[146],"textual":[147],"descriptions":[148],"augmented":[149],"with":[150],"learnable":[151],"context":[152],"prompts,":[153],"serving":[154],"supervision":[156],"signals":[157],"cross-task":[159],"alignment":[160],"anchors":[161],"space;":[166],"(3)":[168],"Dynamic":[170],"Prior":[171],"(DPM)":[173],"module":[174],"incorporates":[176],"prior":[177],"derived":[179],"the":[181],"Action":[183],"Coding":[184],"System":[185],"data-driven":[189],"association":[190],"matrix":[191],"high-level":[194],"feature":[195],"space,":[196],"enabling":[197],"explicit":[198],"transfer.":[202],"Extensive":[203],"experiments":[204],"popular":[206],"benchmarks":[212],"show":[213],"achieves":[216],"state-of-the-art":[217],"performance":[218],"both":[220],"tasks":[221],"simultaneously,":[222],"demonstrate":[224],"semantics":[228],"turn":[231],"enhance":[232],"even":[236],"across":[237],"datasets.":[239]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}