{"id":"https://openalex.org/W4408345796","doi":"https://doi.org/10.1109/icassp49660.2025.10888764","title":"KLMN: Knowledge distillation based lightweight multi-clue image forgery detection and localization","display_name":"KLMN: Knowledge distillation based lightweight multi-clue image forgery detection and localization","publication_year":2025,"publication_date":"2025-03-12","ids":{"openalex":"https://openalex.org/W4408345796","doi":"https://doi.org/10.1109/icassp49660.2025.10888764"},"language":"en","primary_location":{"id":"doi:10.1109/icassp49660.2025.10888764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5057634513","display_name":"Heng Huang","orcid":"https://orcid.org/0000-0003-3036-2961"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng Huang","raw_affiliation_strings":["University of Science and Technology of China,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101726423","display_name":"Yaqi Liu","orcid":"https://orcid.org/0000-0002-1281-9182"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaqi Liu","raw_affiliation_strings":["Beijing Electronic Science and Technology of Institute,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Electronic Science and Technology of Institute,Beijing,China","institution_ids":["https://openalex.org/I202334528"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100641352","display_name":"Xin Jin","orcid":"https://orcid.org/0000-0003-3873-1653"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Jin","raw_affiliation_strings":["Beijing Electronic Science and Technology of Institute,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Electronic Science and Technology of Institute,Beijing,China","institution_ids":["https://openalex.org/I202334528"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100943942","display_name":"Song Xiao","orcid":"https://orcid.org/0009-0006-8142-0921"},"institutions":[{"id":"https://openalex.org/I202334528","display_name":"Beijing Electronic Science and Technology Institute","ror":"https://ror.org/01xdzh226","country_code":"CN","type":"education","lineage":["https://openalex.org/I202334528"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Song Xiao","raw_affiliation_strings":["Beijing Electronic Science and Technology of Institute,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Electronic Science and Technology of Institute,Beijing,China","institution_ids":["https://openalex.org/I202334528"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045778373","display_name":"\u658c \u5218","orcid":"https://orcid.org/0000-0002-1011-2909"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bin Liu","raw_affiliation_strings":["University of Science and Technology of China,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China,China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9934999942779541,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9934999942779541,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.932699978351593,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.9121000170707703,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.6816524863243103},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.6699898838996887},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6018664240837097},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5353648662567139},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5283958315849304},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37578141689300537},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.12241411209106445},{"id":"https://openalex.org/keywords/chromatography","display_name":"Chromatography","score":0.11834436655044556}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6816524863243103},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.6699898838996887},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6018664240837097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5353648662567139},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5283958315849304},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37578141689300537},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.12241411209106445},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.11834436655044556}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp49660.2025.10888764","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp49660.2025.10888764","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.41999998688697815,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W1983586459","https://openalex.org/W1985729543","https://openalex.org/W2009130368","https://openalex.org/W2055745001","https://openalex.org/W2080264113","https://openalex.org/W2096076665","https://openalex.org/W2104116677","https://openalex.org/W2111374353","https://openalex.org/W2164990255","https://openalex.org/W2169439181","https://openalex.org/W2412509443","https://openalex.org/W2518397542","https://openalex.org/W2888338418","https://openalex.org/W2895286859","https://openalex.org/W2912648825","https://openalex.org/W2994855290","https://openalex.org/W3027377338","https://openalex.org/W3035392229","https://openalex.org/W3105676814","https://openalex.org/W3154575015","https://openalex.org/W3179308556","https://openalex.org/W3189718486","https://openalex.org/W3197106219","https://openalex.org/W3211490618","https://openalex.org/W4225554547","https://openalex.org/W4292828490","https://openalex.org/W4312981036","https://openalex.org/W4313121508","https://openalex.org/W4386075803","https://openalex.org/W4386075856","https://openalex.org/W6795140394"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Current":[0],"image":[1,6,39],"forensics":[2],"methods":[3],"often":[4],"utilize":[5],"features":[7,18,63],"from":[8,106],"various":[9,70],"frequency":[10],"domains.":[11],"However,":[12],"the":[13,76,88,107,136],"effective":[14],"use":[15],"of":[16,29,72,78],"these":[17],"frequently":[19],"depends":[20],"on":[21,53,118],"complex":[22],"network":[23,44],"architectures":[24],"and":[25,42,110,127,130,141],"a":[26,36,48,83],"large":[27],"number":[28,77],"parameters.":[30,79],"In":[31],"this":[32],"paper,":[33],"we":[34],"introduce":[35],"lightweight":[37],"Multi-Clue":[38],"forgery":[40,73],"detection":[41],"localization":[43],"(KLMN)":[45],"along":[46],"with":[47,64],"novel":[49],"extractor-adapter":[50,58],"framework":[51,59],"based":[52],"multi-target":[54,95],"knowledge":[55,96],"distillation.":[56],"Our":[57],"effectively":[60],"integrates":[61],"RGB":[62],"low-level":[65],"features,":[66],"enhancing":[67],"resilience":[68],"against":[69],"forms":[71],"while":[74,134],"reducing":[75],"We":[80],"also":[81],"propose":[82],"feature-aggregated":[84],"decoder":[85],"that":[86,122],"reconstructs":[87],"predicted":[89,103],"mask":[90],"by":[91],"remixing":[92],"features.":[93],"The":[94],"distillation":[97,105],"process":[98],"includes":[99],"intermediate":[100],"feature":[101],"distillation,":[102],"map":[104],"teacher":[108],"networks,":[109],"supervised":[111],"training":[112],"using":[113],"ground":[114],"truths.":[115],"Experimental":[116],"results":[117],"multiple":[119],"datasets":[120],"demonstrate":[121],"our":[123],"approach":[124],"can":[125],"accurately":[126],"efficiently":[128],"detect":[129],"localize":[131],"manipulated":[132],"regions":[133],"meeting":[135],"requirements":[137],"for":[138],"fewer":[139],"parameters":[140],"reduced":[142],"memory":[143],"usage.":[144]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}