{"id":"https://openalex.org/W4304015018","doi":"https://doi.org/10.1145/3503161.3548421","title":"High-Quality 3D Face Reconstruction with Affine Convolutional Networks","display_name":"High-Quality 3D Face Reconstruction with Affine Convolutional Networks","publication_year":2022,"publication_date":"2022-10-10","ids":{"openalex":"https://openalex.org/W4304015018","doi":"https://doi.org/10.1145/3503161.3548421"},"language":"en","primary_location":{"id":"doi:10.1145/3503161.3548421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548421","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2310.14237","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5080934148","display_name":"Zhiqian Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhiqian Lin","raw_affiliation_strings":["Zhejiang University, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049770988","display_name":"Jiangke Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangke Lin","raw_affiliation_strings":["NetEase Fuxi AI Lab, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"NetEase Fuxi AI Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019036797","display_name":"Lincheng Li","orcid":"https://orcid.org/0000-0002-6047-0472"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lincheng Li","raw_affiliation_strings":["NetEase Fuxi AI Lab, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"NetEase Fuxi AI Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100638623","display_name":"Yi Yuan","orcid":"https://orcid.org/0000-0003-2507-8181"},"institutions":[{"id":"https://openalex.org/I4210091137","display_name":"NetEase (China)","ror":"https://ror.org/00fp6fj05","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210091137"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Yuan","raw_affiliation_strings":["NetEase Fuxi AI Lab, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"NetEase Fuxi AI Lab, Hangzhou, China","institution_ids":["https://openalex.org/I4210091137"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088611151","display_name":"Zhengxia Zou","orcid":"https://orcid.org/0000-0003-1774-552X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengxia Zou","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5080934148"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.4786,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.73165366,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2495","last_page":"2503"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9916999936103821,"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/affine-transformation","display_name":"Affine transformation","score":0.7440948486328125},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.734499454498291},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6489850878715515},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5917108058929443},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5863370895385742},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5117006301879883},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48923659324645996},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4872826337814331},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.4290798604488373},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42635682225227356},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4039371907711029},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3675808310508728},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2055630087852478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1740647554397583}],"concepts":[{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.7440948486328125},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.734499454498291},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6489850878715515},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5917108058929443},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5863370895385742},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5117006301879883},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48923659324645996},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4872826337814331},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.4290798604488373},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42635682225227356},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4039371907711029},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3675808310508728},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2055630087852478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1740647554397583},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3503161.3548421","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3503161.3548421","pdf_url":null,"source":{"id":"https://openalex.org/S4363608757","display_name":"Proceedings of the 30th ACM International Conference on Multimedia","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM International Conference on Multimedia","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2310.14237","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.14237","pdf_url":"https://arxiv.org/pdf/2310.14237","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2310.14237","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2310.14237","pdf_url":"https://arxiv.org/pdf/2310.14237","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.75,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4304015018.pdf","grobid_xml":"https://content.openalex.org/works/W4304015018.grobid-xml"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W2017107803","https://openalex.org/W2107037917","https://openalex.org/W2237250383","https://openalex.org/W2277958045","https://openalex.org/W2431101926","https://openalex.org/W2555510177","https://openalex.org/W2562066862","https://openalex.org/W2601564443","https://openalex.org/W2769666294","https://openalex.org/W2771328060","https://openalex.org/W2798291180","https://openalex.org/W2912459656","https://openalex.org/W2945729334","https://openalex.org/W2962860871","https://openalex.org/W2962922861","https://openalex.org/W2963342110","https://openalex.org/W2963409406","https://openalex.org/W2963460857","https://openalex.org/W2963527086","https://openalex.org/W2963557052","https://openalex.org/W2963800363","https://openalex.org/W2964449965","https://openalex.org/W2966926453","https://openalex.org/W2990173985","https://openalex.org/W3034512702","https://openalex.org/W3034798648","https://openalex.org/W3035104236","https://openalex.org/W3035413889","https://openalex.org/W3035523051","https://openalex.org/W3092521131","https://openalex.org/W3101531717","https://openalex.org/W3104300620","https://openalex.org/W3111487461","https://openalex.org/W3126799216","https://openalex.org/W3175010531","https://openalex.org/W3180195040","https://openalex.org/W3180794345","https://openalex.org/W3185889280","https://openalex.org/W4297813700","https://openalex.org/W4301409532","https://openalex.org/W6618372016"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W3135697610","https://openalex.org/W4390516098","https://openalex.org/W2085033728","https://openalex.org/W4285411112","https://openalex.org/W2171299904","https://openalex.org/W2181948922","https://openalex.org/W2384362569","https://openalex.org/W1647606319","https://openalex.org/W2964954556"],"abstract_inverted_index":{"Recent":[0],"works":[1],"based":[2,84],"on":[3],"convolutional":[4],"encoder-decoder":[5],"architecture":[6],"and":[7,35,52,91,94,149,176],"3DMM":[8],"parameterization":[9],"have":[10],"shown":[11],"great":[12],"potential":[13],"for":[14,117,141,146,152],"canonical":[15],"view":[16],"reconstruction":[17],"from":[18,27,112],"a":[19,72],"single":[20],"input":[21,34,48,90],"image.":[22],"Conventional":[23],"CNN":[24,83],"architectures":[25],"benefit":[26],"exploiting":[28],"the":[29,33,43,47,53,57,77,100,113,122,159,163,206],"spatial":[30,44,119],"correspondence":[31],"between":[32,46],"output":[36,55,92,98],"pixels.":[37],"However,":[38],"in":[39,132,158],"3D":[40,129],"face":[41],"reconstruction,":[42],"misalignment":[45],"image":[49],"(e.g.":[50],"face)":[51],"canonical/UV":[54],"makes":[56],"feature":[58,123],"encoding-decoding":[59],"process":[60],"quite":[61],"challenging.":[62],"In":[63,103,125],"this":[64,68],"paper,":[65],"to":[66,86],"tackle":[67],"problem,":[69],"we":[70,127],"propose":[71],"new":[73],"network":[74],"architecture,":[75],"namely":[76],"Affine":[78],"Convolution":[79],"Networks,":[80],"which":[81],"enables":[82],"approaches":[85,191],"handle":[87],"spatially":[88],"non-corresponding":[89],"images":[93],"maintain":[95],"high-fidelity":[96],"quality":[97],"at":[99,182],"same":[101],"time.":[102],"our":[104],"method,":[105],"an":[106],"affine":[107,114],"transformation":[108],"matrix":[109],"is":[110,174],"learned":[111],"convolution":[115],"layer":[116],"each":[118],"location":[120],"of":[121,184],"maps.":[124],"addition,":[126],"represent":[128],"human":[130],"heads":[131],"UV":[133,180],"space":[134],"with":[135],"multiple":[136],"components,":[137],"including":[138],"diffuse":[139],"maps":[140,145,151,181],"texture":[142],"representation,":[143,148],"position":[144],"geometry":[147],"light":[150],"recovering":[153],"more":[154],"complex":[155],"lighting":[156],"conditions":[157],"real":[160],"world.":[161],"All":[162],"components":[164],"can":[165,177],"be":[166,203],"trained":[167],"without":[168],"any":[169],"manual":[170],"annotations.":[171],"Our":[172,200],"method":[173],"parametric-free":[175],"generate":[178,193],"high-quality":[179],"resolution":[183],"512":[185,187],"x":[186,195],"pixels,":[188],"while":[189],"previous":[190],"normally":[192],"256":[194,196],"pixels":[197],"or":[198],"smaller.":[199],"code":[201],"will":[202],"released":[204],"once":[205],"paper":[207],"got":[208],"accepted.":[209]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}