{"id":"https://openalex.org/W7118357728","doi":"https://doi.org/10.48550/arxiv.2601.00789","title":"Fusion-SSAT: Unleashing the Potential of Self-supervised Auxiliary Task by Feature Fusion for Generalized Deepfake Detection","display_name":"Fusion-SSAT: Unleashing the Potential of Self-supervised Auxiliary Task by Feature Fusion for Generalized Deepfake Detection","publication_year":2026,"publication_date":"2026-01-02","ids":{"openalex":"https://openalex.org/W7118357728","doi":"https://doi.org/10.48550/arxiv.2601.00789"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.00789","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00789","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.00789","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5104348030","display_name":"Shukesh Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Reddy, Shukesh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057061455","display_name":"Srijan Das","orcid":"https://orcid.org/0000-0002-3373-6749"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Srijan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5122015322","display_name":"Abhijit Das","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Das, Abhijit","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5104348030"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.7581999897956848,"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":0.7581999897956848,"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":0.04270000010728836,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.031599998474121094,"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/representation","display_name":"Representation (politics)","score":0.6693000197410583},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6326000094413757},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6036999821662903},{"id":"https://openalex.org/keywords/generalizability-theory","display_name":"Generalizability theory","score":0.6029999852180481},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5870000123977661},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5566999912261963},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4724000096321106}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6913999915122986},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6764000058174133},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6693000197410583},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6326000094413757},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6036999821662903},{"id":"https://openalex.org/C27158222","wikidata":"https://www.wikidata.org/wiki/Q5532422","display_name":"Generalizability theory","level":2,"score":0.6029999852180481},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5870000123977661},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5566999912261963},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.519599974155426},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4724000096321106},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.43369999527931213},{"id":"https://openalex.org/C28006648","wikidata":"https://www.wikidata.org/wiki/Q6934509","display_name":"Multi-task learning","level":3,"score":0.38999998569488525},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3610000014305115},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.34209999442100525},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2948000133037567},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.26759999990463257}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.00789","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00789","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.00789","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.00789","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"work,":[2],"we":[3,29],"attempted":[4],"to":[5],"unleash":[6],"the":[7,19,34,50,63,72,83,92],"potential":[8,74],"of":[9,22,33,81,101],"self-supervised":[10,54,84],"learning":[11],"as":[12],"an":[13],"auxiliary":[14,55],"task":[15,21],"that":[16,40,48],"can":[17,41,70],"optimise":[18],"primary":[20,86,93],"generalised":[23],"deepfake":[24],"detection.":[25],"To":[26],"explore":[27],"this,":[28],"examined":[30],"different":[31],"combinations":[32],"training":[35],"schemes":[36],"for":[37,62,91],"these":[38],"tasks":[39,56],"be":[42],"most":[43],"effective.":[44],"Our":[45],"findings":[46],"reveal":[47],"fusing":[49],"feature":[51,60],"representation":[52,61,69,80],"from":[53],"is":[57],"a":[58,68,78,98],"powerful":[59],"problem":[64],"at":[65],"hand.":[66],"Such":[67],"leverage":[71],"ultimate":[73],"and":[75,85,111],"bring":[76],"in":[77],"unique":[79],"both":[82],"tasks,":[87],"achieving":[88],"better":[89,115],"performance":[90],"task.":[94],"We":[95],"experimented":[96],"on":[97,117],"large":[99],"set":[100],"datasets,":[102],"which":[103],"includes":[104],"DF40,":[105],"FaceForensics++,":[106],"Celeb-DF,":[107],"DFD,":[108],"FaceShifter,":[109],"UADFV,":[110],"our":[112],"results":[113],"showed":[114],"generalizability":[116],"cross-dataset":[118],"evaluation":[119],"when":[120],"compared":[121],"with":[122],"current":[123],"state-of-the-art":[124],"detectors.":[125]},"counts_by_year":[],"updated_date":"2026-01-08T20:10:11.968330","created_date":"2026-01-08T00:00:00"}