{"id":"https://openalex.org/W3035542935","doi":"https://doi.org/10.24963/ijcai.2020/102","title":"G2RL: Geometry-Guided Representation Learning for Facial Action Unit Intensity Estimation","display_name":"G2RL: Geometry-Guided Representation Learning for Facial Action Unit Intensity Estimation","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3035542935","doi":"https://doi.org/10.24963/ijcai.2020/102","mag":"3035542935"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2020/102","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/102","pdf_url":"https://www.ijcai.org/proceedings/2020/0102.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2020/0102.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5072087245","display_name":"Yingruo Fan","orcid":"https://orcid.org/0000-0001-8977-4958"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Yingruo Fan","raw_affiliation_strings":["The University of Hong Kong","Department of Electrical and Electronic Engineering, University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021691940","display_name":"Zhaojiang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhaojiang Lin","raw_affiliation_strings":["Hong Kong University of Science and Technology","Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology","institution_ids":["https://openalex.org/I200769079"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5072087245"],"corresponding_institution_ids":["https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.8827,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.76208455,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"731","last_page":"737"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9991999864578247,"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"}},"topics":[{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9991999864578247,"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/T12301","display_name":"Facial Nerve Paralysis Treatment and Research","score":0.9923999905586243,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9872000217437744,"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/benchmark","display_name":"Benchmark (surveying)","score":0.7170985341072083},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.700954794883728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6231529116630554},{"id":"https://openalex.org/keywords/intensity","display_name":"Intensity (physics)","score":0.604933500289917},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5962168574333191},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.5864509344100952},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5391578674316406},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4757537543773651},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.45300307869911194},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4436839818954468},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3931797742843628},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2918451726436615},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.19273754954338074},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1559177041053772},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.10982269048690796},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10371062159538269}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7170985341072083},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.700954794883728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6231529116630554},{"id":"https://openalex.org/C93038891","wikidata":"https://www.wikidata.org/wiki/Q1061524","display_name":"Intensity (physics)","level":2,"score":0.604933500289917},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5962168574333191},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.5864509344100952},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5391578674316406},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4757537543773651},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.45300307869911194},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4436839818954468},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3931797742843628},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2918451726436615},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.19273754954338074},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1559177041053772},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.10982269048690796},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10371062159538269},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.24963/ijcai.2020/102","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/102","pdf_url":"https://www.ijcai.org/proceedings/2020/0102.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.hkust.edu.hk:1783.1-110163","is_oa":false,"landing_page_url":"http://lbdiscover.ust.hk/uresolver?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rfr_id=info:sid/HKUST:SPI&rft.genre=article&rft.issn=1045-0823&rft.volume=v. 2021-January&rft.issue=&rft.date=2020&rft.spage=731&rft.aulast=Fan&rft.aufirst=Y.&rft.atitle=G2RL%3A+Geometry-guided+representation+learning+for+facial+action+unit+intensity+estimation&rft.title=IJCAI+International+Joint+Conference+on+Artificial+Intelligence","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference paper"},{"id":"pmh:oai:repository.ust.hk:1783.1-110163","is_oa":false,"landing_page_url":"http://repository.ust.hk/ir/Record/1783.1-110163","pdf_url":null,"source":{"id":"https://openalex.org/S4306401796","display_name":"Rare & Special e-Zone (The Hong Kong University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I200769079","host_organization_name":"Hong Kong University of Science and Technology","host_organization_lineage":["https://openalex.org/I200769079"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference paper"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2020/102","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2020/102","pdf_url":"https://www.ijcai.org/proceedings/2020/0102.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035542935.pdf","grobid_xml":"https://content.openalex.org/works/W3035542935.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1900346672","https://openalex.org/W1964277727","https://openalex.org/W2033702744","https://openalex.org/W2045472600","https://openalex.org/W2051297709","https://openalex.org/W2081749143","https://openalex.org/W2194775991","https://openalex.org/W2217426128","https://openalex.org/W2430562337","https://openalex.org/W2474166357","https://openalex.org/W2560609797","https://openalex.org/W2613192286","https://openalex.org/W2798764454","https://openalex.org/W2799151537","https://openalex.org/W2807107245","https://openalex.org/W2963713173","https://openalex.org/W2964015378","https://openalex.org/W2964322530","https://openalex.org/W2964327872","https://openalex.org/W2969059826","https://openalex.org/W2970303069","https://openalex.org/W3019325883","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W2184606824"],"abstract_inverted_index":{"Facial":[0],"action":[1],"unit":[2],"(AU)":[3],"intensity":[4,10,61,139],"estimation":[5],"aims":[6],"to":[7,27,39,100],"measure":[8],"the":[9,31,75,92,97,102,124,129],"of":[11,43,131],"different":[12,40],"facial":[13,59,137],"muscle":[14],"movements.":[15],"The":[16,110],"external":[17,93,133],"knowledge":[18,95,135],"such":[19],"as":[20],"AU":[21,32,60,83,138],"co-occurrence":[22],"relationship":[23],"is":[24,67,121],"typically":[25],"leveraged":[26],"improve":[28],"performance.":[29],"However,":[30],"characteristics":[33],"may":[34],"vary":[35],"among":[36],"individuals":[37],"due":[38],"physiological":[41],"structures":[42],"human":[44],"faces.":[45],"To":[46],"this":[47],"end,":[48],"we":[49,90],"propose":[50],"a":[51,70,106],"novel":[52],"geometry-guided":[53],"representation":[54],"learning":[55],"(G2RL)":[56],"method":[57,120],"for":[58,136],"estimation.":[62,140],"Specifically,":[63],"our":[64,119],"backbone":[65,98],"model":[66,99],"based":[68],"on":[69,113],"heatmap":[71],"regression":[72],"framework,":[73],"where":[74],"produced":[76],"heatmaps":[77],"reflect":[78],"rich":[79],"information":[80],"associated":[81],"with":[82,123],"intensities":[84],"and":[85,127],"their":[86],"spatial":[87],"distributions.":[88],"Besides,":[89],"incorporate":[91],"geometric":[94,134],"into":[96],"guide":[101],"training":[103],"process":[104],"via":[105],"learned":[107],"projection":[108],"matrix.":[109],"experimental":[111],"results":[112],"two":[114],"benchmark":[115],"datasets":[116],"demonstrate":[117],"that":[118],"comparable":[122],"state-of-the-art":[125],"approaches,":[126],"validate":[128],"effectiveness":[130],"incorporating":[132]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
