{"id":"https://openalex.org/W4387623688","doi":"https://doi.org/10.1109/tce.2023.3323684","title":"3-D Facial Priors Guided Local\u2013Global Motion Collaboration Transforms for One-Shot Talking-Head Video Synthesis","display_name":"3-D Facial Priors Guided Local\u2013Global Motion Collaboration Transforms for One-Shot Talking-Head Video Synthesis","publication_year":2023,"publication_date":"2023-10-13","ids":{"openalex":"https://openalex.org/W4387623688","doi":"https://doi.org/10.1109/tce.2023.3323684"},"language":"en","primary_location":{"id":"doi:10.1109/tce.2023.3323684","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2023.3323684","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-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/A5011358962","display_name":"Yilei Chen","orcid":"https://orcid.org/0000-0003-1957-7099"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yilei Chen","raw_affiliation_strings":["School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-1957-7099","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101774111","display_name":"Rui Zeng","orcid":"https://orcid.org/0000-0003-0155-1288"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Zeng","raw_affiliation_strings":["School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011707621","display_name":"Shengwu Xiong","orcid":"https://orcid.org/0000-0002-4006-7029"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengwu Xiong","raw_affiliation_strings":["Sanya Science and Education Innovation Park, Wuhan University of Technology, Hainan, China"],"raw_orcid":"https://orcid.org/0000-0002-4006-7029","affiliations":[{"raw_affiliation_string":"Sanya Science and Education Innovation Park, Wuhan University of Technology, Hainan, China","institution_ids":["https://openalex.org/I196699116"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I196699116"],"apc_list":null,"apc_paid":null,"fwci":0.3191,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57593173,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"70","issue":"1","first_page":"132","last_page":"143"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9995999932289124,"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":0.9995999932289124,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9976999759674072,"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/T10860","display_name":"Speech and Audio Processing","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8172630667686462},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7385272979736328},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6527091264724731},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5825309157371521},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5255450010299683},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4921650290489197},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.46760621666908264},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.416595458984375},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33606693148612976},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2440989911556244},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11832067370414734}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8172630667686462},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7385272979736328},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6527091264724731},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5825309157371521},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5255450010299683},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4921650290489197},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.46760621666908264},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.416595458984375},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33606693148612976},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2440989911556244},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11832067370414734},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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":1,"locations":[{"id":"doi:10.1109/tce.2023.3323684","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tce.2023.3323684","pdf_url":null,"source":{"id":"https://openalex.org/S126824455","display_name":"IEEE Transactions on Consumer Electronics","issn_l":"0098-3063","issn":["0098-3063","1558-4127"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Consumer Electronics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G4653825012","display_name":null,"funder_award_id":"62176194","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7169761342","display_name":null,"funder_award_id":"2023BAB083","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":84,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2017107803","https://openalex.org/W2105649179","https://openalex.org/W2107037917","https://openalex.org/W2147885303","https://openalex.org/W2237250383","https://openalex.org/W2301937176","https://openalex.org/W2348664362","https://openalex.org/W2412002662","https://openalex.org/W2579578355","https://openalex.org/W2594690981","https://openalex.org/W2604233003","https://openalex.org/W2604379605","https://openalex.org/W2726515241","https://openalex.org/W2738406145","https://openalex.org/W2769654144","https://openalex.org/W2776121517","https://openalex.org/W2804621595","https://openalex.org/W2806833697","https://openalex.org/W2808631503","https://openalex.org/W2883127586","https://openalex.org/W2883861033","https://openalex.org/W2902266071","https://openalex.org/W2902836694","https://openalex.org/W2914217321","https://openalex.org/W2944294033","https://openalex.org/W2950689937","https://openalex.org/W2962974533","https://openalex.org/W2963073614","https://openalex.org/W2963290645","https://openalex.org/W2963641969","https://openalex.org/W2964449965","https://openalex.org/W2964559396","https://openalex.org/W2968917279","https://openalex.org/W2971617190","https://openalex.org/W2979894294","https://openalex.org/W2990452356","https://openalex.org/W2991079364","https://openalex.org/W3010434693","https://openalex.org/W3019952993","https://openalex.org/W3023706973","https://openalex.org/W3025498998","https://openalex.org/W3034192160","https://openalex.org/W3081492798","https://openalex.org/W3087121792","https://openalex.org/W3089177030","https://openalex.org/W3097167612","https://openalex.org/W3097792222","https://openalex.org/W3101631197","https://openalex.org/W3102015846","https://openalex.org/W3107666850","https://openalex.org/W3109114891","https://openalex.org/W3119379445","https://openalex.org/W3126434301","https://openalex.org/W3128401974","https://openalex.org/W3177150198","https://openalex.org/W3186090335","https://openalex.org/W3187364420","https://openalex.org/W3195529437","https://openalex.org/W3197199219","https://openalex.org/W3202128205","https://openalex.org/W4200631136","https://openalex.org/W4206517532","https://openalex.org/W4210657261","https://openalex.org/W4214548561","https://openalex.org/W4288391327","https://openalex.org/W4297808394","https://openalex.org/W4307955901","https://openalex.org/W4320005661","https://openalex.org/W6618372016","https://openalex.org/W6637373629","https://openalex.org/W6726983635","https://openalex.org/W6753914649","https://openalex.org/W6754172994","https://openalex.org/W6765779288","https://openalex.org/W6766196973","https://openalex.org/W6767164110","https://openalex.org/W6767264202","https://openalex.org/W6769148693","https://openalex.org/W6774285787","https://openalex.org/W6776963518","https://openalex.org/W6777209069","https://openalex.org/W6844194202"],"related_works":["https://openalex.org/W2560215812","https://openalex.org/W2949601986","https://openalex.org/W2788972299","https://openalex.org/W2521347458","https://openalex.org/W2498789492","https://openalex.org/W2990636717","https://openalex.org/W2972212393","https://openalex.org/W2163164795","https://openalex.org/W2030154815","https://openalex.org/W2051121715"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,7,38,158],"method":[4],"that":[5],"takes":[6],"sequence":[8],"of":[9,101,122,131,144],"audio,":[10],"pose":[11],"source":[12],"video,":[13],"and":[14,48,77,112,148],"one":[15],"reference":[16],"image":[17,176],"as":[18,82,115,139],"input":[19,116,140],"to":[20,71,94,117,135,167,172,184],"generate":[21],"natural":[22],"head":[23,103],"spatial":[24],"movement":[25],"talking":[26],"face":[27,111],"video.":[28],"Based":[29],"on":[30],"the":[31,57,73,78,99,119,129,174,181],"powerful":[32],"3D":[33,65],"Morphable":[34],"Model(3DMM),":[35],"we":[36,69,156],"propose":[37,70,157],"novel":[39],"framework":[40],"comprising":[41],"two":[42],"modules:":[43],"Audio":[44],"Map":[45],"Expression":[46],"Net":[47,92],"Local-Global":[49,87],"Motion":[50,88],"Collaboration":[51,89],"Transforms":[52,90],"Render":[53,91],"Net.":[54],"To":[55],"make":[56],"audio":[58],"map":[59],"expression":[60,67],"network":[61,165],"predict":[62,118],"more":[63],"precise":[64],"facial":[66],"parameters,":[68],"use":[72],"shape":[74],"constraint":[75,80],"loss":[76,81],"lip-sync":[79],"additional":[83],"constraints.":[84],"The":[85],"proposed":[86],"aims":[93],"improve":[95,173],"generalization":[96],"capability":[97],"in":[98],"presence":[100],"apparent":[102],"motion":[104,121,151],"by":[105],"utilizing":[106],"cross-modal":[107,137],"images":[108,138],"(3D":[109],"reconstruction":[110],"realistic":[113],"face)":[114],"residual":[120,150],"pose-aware":[123,145],"dynamic":[124,146],"content.":[125],"Our":[126],"work":[127],"demonstrates":[128],"ability":[130],"Convolutional":[132],"Neural":[133],"Networks":[134],"utilize":[136],"for":[141],"simultaneous":[142],"estimation":[143],"content":[147],"local":[149],"through":[152],"self-supervised":[153],"learning.":[154],"Finally,":[155],"multi-scale":[159],"feature":[160,170],"adaptive":[161],"denormalization":[162],"(FADE)":[163],"U-net":[164],"architecture":[166],"exploit":[168],"coarse-to-fine":[169],"representations":[171],"generated":[175],"quality.":[177],"Experimental":[178],"results":[179],"demonstrate":[180],"effectiveness":[182],"compared":[183],"other":[185],"state-of-the-art":[186],"methods.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
