{"id":"https://openalex.org/W4306313207","doi":"https://doi.org/10.48550/arxiv.2210.07233","title":"Shape Preserving Facial Landmarks with Graph Attention Networks","display_name":"Shape Preserving Facial Landmarks with Graph Attention Networks","publication_year":2022,"publication_date":"2022-10-13","ids":{"openalex":"https://openalex.org/W4306313207","doi":"https://doi.org/10.48550/arxiv.2210.07233"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2210.07233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.07233","pdf_url":"https://arxiv.org/pdf/2210.07233","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2210.07233","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5090552355","display_name":"Andr\u00e9s Prados-Torreblanca","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Prados-Torreblanca, Andr\u00e9s","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034180773","display_name":"Jos\u00e9 M. Buenaposada","orcid":"https://orcid.org/0000-0002-4308-9653"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Buenaposada, Jos\u00e9 M.","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5014943420","display_name":"Luis Baumela","orcid":"https://orcid.org/0000-0001-6910-4359"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baumela, Luis","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5090552355"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"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/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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":0.9998000264167786,"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/T10057","display_name":"Face and Expression Recognition","score":0.9787999987602234,"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":0.9235000014305115,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/landmark","display_name":"Landmark","score":0.9406794309616089},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8145275712013245},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6467942595481873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6416635513305664},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6192970275878906},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5438526272773743},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.50003981590271},{"id":"https://openalex.org/keywords/cascade","display_name":"Cascade","score":0.48436006903648376},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.48246222734451294},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4801616072654724},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.42486029863357544},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.419107586145401},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.21474850177764893}],"concepts":[{"id":"https://openalex.org/C2780297707","wikidata":"https://www.wikidata.org/wiki/Q4895393","display_name":"Landmark","level":2,"score":0.9406794309616089},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8145275712013245},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6467942595481873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6416635513305664},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6192970275878906},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5438526272773743},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.50003981590271},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.48436006903648376},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.48246222734451294},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4801616072654724},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.42486029863357544},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.419107586145401},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.21474850177764893},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2210.07233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.07233","pdf_url":"https://arxiv.org/pdf/2210.07233","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"doi:10.48550/arxiv.2210.07233","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2210.07233","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2210.07233","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.07233","pdf_url":"https://arxiv.org/pdf/2210.07233","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2056853153","https://openalex.org/W2057559274","https://openalex.org/W2005087563","https://openalex.org/W2378111931","https://openalex.org/W2052388267","https://openalex.org/W2950647290","https://openalex.org/W1968481813","https://openalex.org/W2620829895","https://openalex.org/W2356918560","https://openalex.org/W4243161226"],"abstract_inverted_index":{"Top-performing":[0],"landmark":[1,103,133],"estimation":[2],"algorithms":[3],"are":[4],"based":[5,42],"on":[6,43,129],"exploiting":[7],"the":[8,44,67,80,95,110,118,121,150],"excellent":[9],"ability":[10],"of":[11,46,52,71,97,117,120,153],"large":[12,147],"convolutional":[13],"neural":[14],"networks":[15],"(CNNs)":[16],"to":[17,78,83,93],"represent":[18],"local":[19,151],"appearance.":[20],"However,":[21],"it":[22],"is":[23,87,141],"well":[24],"known":[25],"that":[26,64,109],"they":[27],"can":[28],"only":[29],"learn":[30],"weak":[31],"spatial":[32],"relationships.":[33],"To":[34,57],"address":[35],"this":[36,58],"problem,":[37],"we":[38,60],"propose":[39],"a":[40,47,50,90,101,114],"model":[41,112,140],"combination":[45],"CNN":[48],"with":[49,89],"cascade":[51],"Graph":[53],"Attention":[54],"Network":[55],"regressors.":[56],"end,":[59],"introduce":[61],"an":[62,75],"encoding":[63],"jointly":[65],"represents":[66],"appearance":[68,152],"and":[69,74,100,132],"location":[70,96],"facial":[72],"landmarks":[73],"attention":[76],"mechanism":[77],"weigh":[79],"information":[81],"according":[82],"its":[84],"reliability.":[85],"This":[86],"combined":[88],"multi-task":[91],"approach":[92],"initialize":[94],"graph":[98],"nodes":[99],"coarse-to-fine":[102],"description":[104],"scheme.":[105],"Our":[106],"experiments":[107],"confirm":[108],"proposed":[111],"learns":[113],"global":[115],"representation":[116],"structure":[119],"face,":[122],"achieving":[123],"top":[124],"performance":[125],"in":[126,144,149],"popular":[127],"benchmarks":[128],"head":[130],"pose":[131],"estimation.":[134],"The":[135],"improvement":[136],"provided":[137],"by":[138],"our":[139],"most":[142],"significant":[143],"situations":[145],"involving":[146],"changes":[148],"landmarks.":[154]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
