{"id":"https://openalex.org/W4394862914","doi":"https://doi.org/10.1109/lsp.2024.3388958","title":"Towards Generated Image Provenance Analysis via Conceptual-Similar-Guided-SLIP Retrieval","display_name":"Towards Generated Image Provenance Analysis via Conceptual-Similar-Guided-SLIP Retrieval","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4394862914","doi":"https://doi.org/10.1109/lsp.2024.3388958"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2024.3388958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3388958","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5082680996","display_name":"Xiaojie Xia","orcid":"https://orcid.org/0000-0002-6486-7557"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaojie Xia","raw_affiliation_strings":["Fujitsu R&amp;D Cente Company, Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Fujitsu R&amp;D Cente Company, Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022387250","display_name":"Liuan Wang","orcid":"https://orcid.org/0000-0002-5627-7522"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liuan Wang","raw_affiliation_strings":["Fujitsu R&amp;D Cente Company, Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Fujitsu R&amp;D Cente Company, Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100327195","display_name":"Jun Sun","orcid":"https://orcid.org/0000-0002-0967-4859"},"institutions":[{"id":"https://openalex.org/I4210159607","display_name":"Fujitsu (China)","ror":"https://ror.org/04w4yzw62","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210159607"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Sun","raw_affiliation_strings":["Fujitsu R&amp;D Cente Company, Ltd., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Fujitsu R&amp;D Cente Company, Ltd., Beijing, China","institution_ids":["https://openalex.org/I4210159607"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059844018","display_name":"Akira Nakagawa","orcid":"https://orcid.org/0009-0008-1563-1573"},"institutions":[{"id":"https://openalex.org/I2252096349","display_name":"Fujitsu (Japan)","ror":"https://ror.org/038e2g226","country_code":"JP","type":"company","lineage":["https://openalex.org/I2252096349"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Akira Nakagawa","raw_affiliation_strings":["Fujitsu Research, Kawasaki, Japan"],"affiliations":[{"raw_affiliation_string":"Fujitsu Research, Kawasaki, Japan","institution_ids":["https://openalex.org/I2252096349"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5082680996"],"corresponding_institution_ids":["https://openalex.org/I4210159607"],"apc_list":null,"apc_paid":null,"fwci":0.752,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69275721,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"31","issue":null,"first_page":"1419","last_page":"1423"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T11710","display_name":"Biomedical Text Mining and Ontologies","score":0.9779000282287598,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11986","display_name":"Scientific Computing and Data Management","score":0.9725000262260437,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9416999816894531,"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/provenance","display_name":"Provenance","score":0.6811143755912781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5865787863731384},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5298953652381897},{"id":"https://openalex.org/keywords/image-retrieval","display_name":"Image retrieval","score":0.4661131501197815},{"id":"https://openalex.org/keywords/slip","display_name":"Slip (aerodynamics)","score":0.4126732349395752},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.399528831243515},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37873056530952454},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.24943512678146362},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.137971431016922}],"concepts":[{"id":"https://openalex.org/C2780049196","wikidata":"https://www.wikidata.org/wiki/Q23582628","display_name":"Provenance","level":2,"score":0.6811143755912781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5865787863731384},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5298953652381897},{"id":"https://openalex.org/C1667742","wikidata":"https://www.wikidata.org/wiki/Q10927554","display_name":"Image retrieval","level":3,"score":0.4661131501197815},{"id":"https://openalex.org/C195268267","wikidata":"https://www.wikidata.org/wiki/Q1928883","display_name":"Slip (aerodynamics)","level":2,"score":0.4126732349395752},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.399528831243515},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37873056530952454},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.24943512678146362},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.137971431016922},{"id":"https://openalex.org/C5900021","wikidata":"https://www.wikidata.org/wiki/Q163082","display_name":"Petrology","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2024.3388958","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2024.3388958","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W26575457","https://openalex.org/W1966928092","https://openalex.org/W2326180695","https://openalex.org/W2336302573","https://openalex.org/W2519560949","https://openalex.org/W2524324335","https://openalex.org/W2584637367","https://openalex.org/W2751609461","https://openalex.org/W2883725317","https://openalex.org/W2885050713","https://openalex.org/W2889929596","https://openalex.org/W2918316070","https://openalex.org/W2967957126","https://openalex.org/W2981448908","https://openalex.org/W2981537605","https://openalex.org/W2987222078","https://openalex.org/W2994818707","https://openalex.org/W3105475654","https://openalex.org/W3138516171","https://openalex.org/W3159481202","https://openalex.org/W3175759175","https://openalex.org/W3187879352","https://openalex.org/W3205213941","https://openalex.org/W3213100861","https://openalex.org/W4213299273","https://openalex.org/W4214819138","https://openalex.org/W4225665828","https://openalex.org/W4286894632","https://openalex.org/W4287117287","https://openalex.org/W4287367114","https://openalex.org/W4288581820","https://openalex.org/W4306316995","https://openalex.org/W4306820534","https://openalex.org/W4312442470","https://openalex.org/W4312629998","https://openalex.org/W4313156423","https://openalex.org/W4318719586","https://openalex.org/W4386076098","https://openalex.org/W4389195517","https://openalex.org/W6601069402","https://openalex.org/W6758139636","https://openalex.org/W6791353385","https://openalex.org/W6796018650","https://openalex.org/W6803522481","https://openalex.org/W6811013733","https://openalex.org/W6846007759","https://openalex.org/W6849141701"],"related_works":["https://openalex.org/W2354627941","https://openalex.org/W2347483153","https://openalex.org/W2353379336","https://openalex.org/W2379683085","https://openalex.org/W2363868702","https://openalex.org/W2374448931","https://openalex.org/W2376723740","https://openalex.org/W2370535391","https://openalex.org/W2370679613","https://openalex.org/W2380057024"],"abstract_inverted_index":{"With":[0],"the":[1,16,23,58,63,78,91,96,101,115,120,130,135,140],"prevalence":[2],"of":[3,86,142],"state-of-the-art":[4],"generative":[5],"models,":[6],"photorealistic":[7],"synthetic":[8],"images":[9,18,133],"can":[10,28,127],"now":[11],"be":[12],"easily":[13],"generated.":[14],"However,":[15],"generated":[17,59,121,143],"may":[19],"replicate":[20],"contents":[21],"from":[22,134],"original":[24],"training":[25,136],"images,":[26,122],"which":[27,112],"lead":[29],"to":[30,76,80,94,138],"potential":[31],"legal":[32],"issues.":[33],"In":[34],"this":[35],"paper,":[36],"we":[37],"propose":[38],"a":[39,71,82],"novel":[40],"method":[41,93,126],"called":[42],"<italic":[43],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[44],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">Conceptual-Similar-guided":[45],"Self-supervised":[46],"Language-Image":[47],"Pre-training</i>":[48],"(CS-SLIP)":[49],"that":[50,114],"leverages":[51],"both":[52],"image":[53,60,144],"and":[54,67,107,123],"text":[55],"modalities":[56],"for":[57],"provenance.":[61],"Besides":[62],"self-supervised":[64],"learning":[65,69],"branch":[66,73],"contrastive":[68],"branch,":[70],"conceptual-similar":[72],"is":[74],"designed":[75],"guide":[77],"model":[79],"learn":[81],"better":[83],"feature":[84],"representation":[85],"image-text-pairs.":[87],"We":[88],"also":[89],"adopt":[90],"re-ranking":[92],"refine":[95],"initial":[97],"matching":[98],"candidates":[99],"via":[100],"cross-modal":[102],"bi-directional":[103],"retrieval.":[104],"Extensive":[105],"qualitative":[106],"quantitative":[108],"experiments":[109],"are":[110],"conducted,":[111],"demonstrate":[113],"replication":[116],"indeed":[117],"exists":[118],"in":[119],"our":[124],"proposed":[125],"effectively":[128],"retrieve":[129],"most":[131],"similar":[132],"corpus":[137],"achieve":[139],"goal":[141],"provenance":[145],"analysis.":[146]},"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"}
