{"id":"https://openalex.org/W4415709023","doi":"https://doi.org/10.1109/icme59968.2025.11209919","title":"Identity-Preserving Talking Head Cross-Identity Reenactment with Adaptive Structure Normalization","display_name":"Identity-Preserving Talking Head Cross-Identity Reenactment with Adaptive Structure Normalization","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415709023","doi":"https://doi.org/10.1109/icme59968.2025.11209919"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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/A5102017271","display_name":"Jing Zhao","orcid":"https://orcid.org/0000-0003-1746-7275"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhao Jing","raw_affiliation_strings":["BUPT,School of Artificial Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"BUPT,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060471213","display_name":"Hongxia Bie","orcid":"https://orcid.org/0000-0002-3675-8476"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongxia Bie","raw_affiliation_strings":["BUPT,School of Artificial Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"BUPT,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113405509","display_name":"Haobo Lei","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haobo Lei","raw_affiliation_strings":["BUPT,School of Artificial Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"BUPT,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100417458","display_name":"Jiali Wang","orcid":"https://orcid.org/0000-0002-2419-0836"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiali Wang","raw_affiliation_strings":["BUPT,School of Artificial Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"BUPT,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113186207","display_name":"Yichen Zhi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yichen Zhi","raw_affiliation_strings":["BUPT,School of Artificial Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"BUPT,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5077575823","display_name":"Zhisong Bie","orcid":"https://orcid.org/0000-0002-1116-1489"},"institutions":[{"id":"https://openalex.org/I4210100255","display_name":"Beijing Academy of Artificial Intelligence","ror":"https://ror.org/016a74861","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210100255"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhisong Bie","raw_affiliation_strings":["BUPT,School of Artificial Intelligence,Beijing,China"],"affiliations":[{"raw_affiliation_string":"BUPT,School of Artificial Intelligence,Beijing,China","institution_ids":["https://openalex.org/I4210100255"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102017271"],"corresponding_institution_ids":["https://openalex.org/I4210100255"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33982301,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6499999761581421,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.6499999761581421,"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/T11448","display_name":"Face recognition and analysis","score":0.32249999046325684,"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/T11094","display_name":"Face Recognition and Perception","score":0.013500000350177288,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.7245000004768372},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.4832000136375427},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.4196999967098236},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4142000079154968},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.398499995470047}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7398999929428101},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.7245000004768372},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7177000045776367},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6520000100135803},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.4832000136375427},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.4196999967098236},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.398499995470047},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.36970001459121704},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.2567000091075897}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209919","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209919","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","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":15,"referenced_works":["https://openalex.org/W2603777577","https://openalex.org/W2726515241","https://openalex.org/W2949662773","https://openalex.org/W2962793481","https://openalex.org/W4312551330","https://openalex.org/W4386066083","https://openalex.org/W4386066256","https://openalex.org/W4386066799","https://openalex.org/W4386075625","https://openalex.org/W4386159053","https://openalex.org/W4386172464","https://openalex.org/W4389383543","https://openalex.org/W4402715897","https://openalex.org/W4402727609","https://openalex.org/W4405208150"],"related_works":[],"abstract_inverted_index":{"Talking":[0],"Head":[1],"reenactment":[2],"aims":[3,55],"to":[4,12,56,94,113,118],"enable":[5],"a":[6,9,16,49,73,104],"face":[7],"in":[8,15,139,143],"source":[10,112,120],"image":[11],"animate":[13],"motions":[14],"driving":[17,68,85,114,117],"frame.":[18],"Existing":[19],"warping-based":[20],"methods":[21,138],"generally":[22],"utilize":[23],"keypoints":[24,32,69],"or":[25],"landmarks":[26,34],"as":[27],"motion":[28],"representations.":[29],"However,":[30],"the":[31,58,81,84,91,99],"and":[33,115],"inevitably":[35],"contain":[36],"conflicting":[37],"facial":[38],"structure":[39,76],"that":[40,54,79,127],"mislead":[41],"cross-identity":[42,100,144],"reenactment.":[43,147],"In":[44],"this":[45],"paper,":[46],"we":[47,102],"propose":[48,103],"talking":[50,145],"head":[51,146],"generation":[52],"method":[53],"mitigate":[57],"structural":[59,86],"differences":[60],"for":[61,98],"identity-preserving":[62],"by":[63,72,109],"predicting":[64],"structure-adapted":[65],"keypoints.":[66],"The":[67],"are":[70],"adjusted":[71],"proposed":[74],"adaptive":[75],"normalization":[77],"module":[78],"aligns":[80],"statistics":[82],"of":[83,90,133],"features":[87],"with":[88],"those":[89],"source.":[92],"Moreover,":[93],"provide":[95],"paired":[96],"samples":[97],"reenactment,":[101],"well-designed":[105],"cycle":[106],"training":[107],"pipeline":[108],"two":[110,122],"steps,":[111],"reversed":[116],"another":[119],"from":[121],"videos.":[123],"Extensive":[124],"experiments":[125],"demonstrate":[126],"our":[128],"approach":[129],"achieves":[130],"an":[131],"improvement":[132],"approximately":[134],"5%":[135],"over":[136],"state-of-the-art":[137],"identity":[140],"preservation":[141],"metric":[142]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-30T00:00:00"}