{"id":"https://openalex.org/W4387760641","doi":"https://doi.org/10.1145/3607829.3616446","title":"GLEFFN: A Global-Local Event Feature Fusion Network for Micro-Expression Recognition","display_name":"GLEFFN: A Global-Local Event Feature Fusion Network for Micro-Expression Recognition","publication_year":2023,"publication_date":"2023-10-18","ids":{"openalex":"https://openalex.org/W4387760641","doi":"https://doi.org/10.1145/3607829.3616446"},"language":"en","primary_location":{"id":"doi:10.1145/3607829.3616446","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3607829.3616446","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis","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/A5063010018","display_name":"Cunhan Guo","orcid":"https://orcid.org/0000-0002-4546-3928"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cunhan Guo","raw_affiliation_strings":["University of Chinese Academy of Sciences & Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4546-3928","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences & Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I4210165038","https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087631670","display_name":"Heyan Huang","orcid":"https://orcid.org/0000-0002-0320-7520"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyan Huang","raw_affiliation_strings":["University of Chinese Academy of Sciences & Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0320-7520","affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences & Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I4210165038","https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5063010018"],"corresponding_institution_ids":["https://openalex.org/I125839683","https://openalex.org/I4210165038"],"apc_list":null,"apc_paid":null,"fwci":3.2339,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.92311746,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"17","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9962999820709229,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9926999807357788,"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/computer-science","display_name":"Computer science","score":0.7393123507499695},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6385905742645264},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6334757804870605},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5974911451339722},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5700305104255676},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.5104418992996216},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48037227988243103},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4425760507583618},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4359495937824249},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4357200264930725},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4237004220485687},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33258238434791565},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09486988186836243},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.0788356363773346}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7393123507499695},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6385905742645264},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6334757804870605},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5974911451339722},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5700305104255676},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.5104418992996216},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48037227988243103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4425760507583618},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4359495937824249},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4357200264930725},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4237004220485687},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33258238434791565},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09486988186836243},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0788356363773346},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3607829.3616446","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3607829.3616446","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd Workshop on Facial Micro-Expression: Advanced Techniques for Multi-Modal Facial Expression Analysis","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1616262590","https://openalex.org/W2006426145","https://openalex.org/W2113977317","https://openalex.org/W2139916508","https://openalex.org/W2237362194","https://openalex.org/W2426188534","https://openalex.org/W2527254703","https://openalex.org/W2808064875","https://openalex.org/W2911617386","https://openalex.org/W2956286548","https://openalex.org/W2958471948","https://openalex.org/W2959679536","https://openalex.org/W2962162344","https://openalex.org/W2963093735","https://openalex.org/W2963420686","https://openalex.org/W2970981431","https://openalex.org/W3080756971","https://openalex.org/W3102431071","https://openalex.org/W3182710365","https://openalex.org/W4283372964","https://openalex.org/W4296204322"],"related_works":["https://openalex.org/W4386083130","https://openalex.org/W2023355163","https://openalex.org/W2117442182","https://openalex.org/W3111737715","https://openalex.org/W2069571255","https://openalex.org/W2081707527","https://openalex.org/W4385998088","https://openalex.org/W3125517176","https://openalex.org/W4367623556","https://openalex.org/W1975907365"],"abstract_inverted_index":{"Micro-expressions":[0],"are":[1,102],"facial":[2],"movements":[3],"of":[4,23,30,154],"short":[5],"duration":[6],"and":[7,43,96,108,158],"low":[8,20,44],"amplitude,":[9],"which,":[10],"upon":[11],"analysis,":[12],"can":[13],"reveal":[14],"genuine":[15],"human":[16],"emotions.":[17],"However,":[18],"the":[19,27,49,65,79,92,97,111,118,136,142,151],"frame":[21,41],"rate":[22],"frame-based":[24],"cameras":[25],"hinders":[26],"further":[28],"advancement":[29],"micro-expression":[31],"recognition":[32],"(MER).":[33],"A":[34],"novel":[35],"technology,":[36],"event-based":[37,155],"cameras,":[38],"boasting":[39],"high":[40],"rates":[42],"latency,":[45],"proves":[46],"suitable":[47],"for":[48,161],"MER":[50,112,143],"task":[51,144],"but":[52],"remains":[53],"challenging":[54],"to":[55,104,140],"obtain.":[56],"In":[57],"this":[58,133],"article,":[59],"a":[60,83],"local":[61,66,93],"event":[62,85,147],"feature,":[63],"namely":[64],"count":[67,94],"image,":[68],"is":[69,73,89],"proposed.":[70],"This":[71],"feature":[72,86],"calculated":[74],"from":[75,145],"up-sampled":[76],"video":[77],"using":[78],"SloMo":[80],"method.":[81],"Additionally,":[82],"global-local":[84],"fusion":[87],"network":[88],"constructed,":[90],"wherein":[91],"image":[95],"global":[98],"dense":[99],"optical":[100],"flow":[101],"merged":[103],"map":[105],"deeper":[106],"features":[107],"effectively":[109],"address":[110],"task.":[113],"Experimental":[114],"results":[115],"demonstrate":[116],"that":[117,132],"proposed":[119],"light-weighted":[120],"method":[121],"outperforms":[122],"state-of-the-art":[123],"approaches":[124],"across":[125],"multiple":[126],"datasets.":[127],"To":[128],"our":[129],"best":[130],"knowledges":[131],"work":[134],"marks":[135],"first":[137],"successful":[138],"attempt":[139],"solve":[141],"an":[146],"perspective,":[148],"thus":[149],"facilitating":[150],"future":[152,162],"promotion":[153],"camera":[156],"technology":[157],"providing":[159],"inspiration":[160],"research":[163],"endeavors":[164],"in":[165],"related":[166],"domains.":[167]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}