{"id":"https://openalex.org/W7133346843","doi":"https://doi.org/10.1109/ijcb65343.2025.11411017","title":"Growing to Detect: A Dynamic Prototype Tree with Structured Replay for Incremental Deepfake Detection","display_name":"Growing to Detect: A Dynamic Prototype Tree with Structured Replay for Incremental Deepfake Detection","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W7133346843","doi":"https://doi.org/10.1109/ijcb65343.2025.11411017"},"language":null,"primary_location":{"id":"doi:10.1109/ijcb65343.2025.11411017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","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/A5104331453","display_name":"Siyu Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siyu Liu","raw_affiliation_strings":["Anhui University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127964049","display_name":"Junxian Duan","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junxian Duan","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128030526","display_name":"Jie Cao","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Cao","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122887395","display_name":"Aihua Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Aihua Zheng","raw_affiliation_strings":["Anhui University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Anhui University","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5127914573","display_name":"Ran He","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ran He","raw_affiliation_strings":["Chinese Academy of Sciences,Institute of Automation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences,Institute of Automation","institution_ids":["https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66626188,"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":"9"},"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":0.9355000257492065,"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":0.9355000257492065,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.01119999960064888,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.007600000128149986,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/key","display_name":"Key (lock)","score":0.5734000205993652},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.5555999875068665},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5157999992370605},{"id":"https://openalex.org/keywords/swap","display_name":"Swap (finance)","score":0.47119998931884766},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.4453999996185303},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4000999927520752}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8235999941825867},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5734000205993652},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.5555999875068665},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5479999780654907},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5157999992370605},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5097000002861023},{"id":"https://openalex.org/C99821215","wikidata":"https://www.wikidata.org/wiki/Q1136583","display_name":"Swap (finance)","level":2,"score":0.47119998931884766},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.4453999996185303},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4000999927520752},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.37220001220703125},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3221000134944916},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2985999882221222},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.28540000319480896},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C109747225","wikidata":"https://www.wikidata.org/wiki/Q815758","display_name":"Scarcity","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb65343.2025.11411017","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411017","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.4973127543926239}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335581","display_name":"Young Scientists Fund","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2102715376","https://openalex.org/W2341528187","https://openalex.org/W2531409750","https://openalex.org/W2963938081","https://openalex.org/W2982058372","https://openalex.org/W3034713808","https://openalex.org/W3092879151","https://openalex.org/W3094728142","https://openalex.org/W3107810305","https://openalex.org/W3108274592","https://openalex.org/W3154326567","https://openalex.org/W3158353280","https://openalex.org/W3168149265","https://openalex.org/W3174508664","https://openalex.org/W3174814557","https://openalex.org/W3180392831","https://openalex.org/W3182523681","https://openalex.org/W4226024856","https://openalex.org/W4313127140","https://openalex.org/W4382119399","https://openalex.org/W4386075501","https://openalex.org/W4386076635","https://openalex.org/W4387947302","https://openalex.org/W4388189737","https://openalex.org/W4389890887","https://openalex.org/W4390871965","https://openalex.org/W4392450481","https://openalex.org/W4404207469","https://openalex.org/W4404450291"],"related_works":[],"abstract_inverted_index":{"The":[0,77,113],"rapid":[1],"advancement":[2],"of":[3,26,38,45,126,154],"deepfake":[4],"technology":[5],"poses":[6],"significant":[7],"threats":[8],"to":[9,19,88,91,162],"social":[10],"trust.":[11],"Recent":[12],"research":[13],"has":[14],"improved":[15],"detectors":[16],"by":[17,119,148],"adapting":[18],"emerging":[20],"deepfakes":[21],"using":[22],"a":[23,54,84],"limited":[24],"number":[25],"samples":[27,146],"through":[28,83,123],"incremental":[29],"learning.":[30],"However,":[31],"these":[32],"approaches":[33],"often":[34],"overlook":[35],"the":[36,64,71,102,124,157],"scarcity":[37],"novel":[39],"samples,":[40],"resulting":[41],"in":[42],"insufficient":[43],"learning":[44,109],"forgery":[46,111],"patterns.":[47,112],"To":[48],"overcome":[49],"this":[50],"challenge,":[51],"we":[52],"propose":[53],"Replay-based":[55],"Dynamic":[56,65],"Prototype":[57,66],"Network":[58],"that":[59,132],"integrates":[60],"two":[61],"key":[62],"modules:":[63],"Tree":[67],"(DPT)":[68],"module":[69,79],"and":[70],"Similarity":[72],"Subtree":[73],"Replay":[74],"(SSR)":[75],"strategy.":[76],"DPT":[78],"dynamically":[80],"introduces":[81],"prototypes":[82,96,107],"hierarchical":[85],"tree":[86],"structure":[87],"effectively":[89],"adapt":[90],"new":[92,110],"deepfakes.":[93],"It":[94],"expands":[95],"based":[97],"on":[98,142,156],"similarity,":[99],"thereby":[100],"retaining":[101],"knowledge":[103],"learned":[104,121],"from":[105,160],"previous":[106],"while":[108],"SSR":[114],"strategy":[115],"mitigates":[116],"catastrophic":[117],"forgetting":[118],"stabilizing":[120],"features":[122],"replay":[125],"relevant":[127],"subtrees.":[128],"Experimental":[129],"results":[130],"demonstrate":[131],"our":[133],"approach":[134],"outperforms":[135],"existing":[136],"methods":[137],"across":[138],"five":[139],"datasets,":[140],"particularly":[141],"high-quality":[143],"face":[144],"swap":[145],"generated":[147],"diffusion-based":[149],"methods,":[150],"achieving":[151],"an":[152],"AUC":[153],"85.86%":[155],"cross-dataset":[158],"task":[159],"FaceForensics++":[161],"DiffSwap.":[163]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-04T00:00:00"}