{"id":"https://openalex.org/W4411599606","doi":"https://doi.org/10.1109/access.2025.3582756","title":"Regularization for Unconditional Image Diffusion Models via Shifted Data Augmentation","display_name":"Regularization for Unconditional Image Diffusion Models via Shifted Data Augmentation","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4411599606","doi":"https://doi.org/10.1109/access.2025.3582756"},"language":"en","primary_location":{"id":"doi:10.1109/access.2025.3582756","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3582756","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2025.3582756","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102774458","display_name":"Kensuke Nakamura","orcid":"https://orcid.org/0000-0002-6858-3551"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kensuke Nakamura","raw_affiliation_strings":["Artificial Intelligence Department, Chung-Ang University, Seoul, South Korea","Computer Science Department, Chung-Ang University, Seoul, Korea"],"raw_orcid":"https://orcid.org/0000-0002-6858-3551","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Department, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Computer Science Department, Chung-Ang University, Seoul, Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064942426","display_name":"Bong-Soo Sohn","orcid":"https://orcid.org/0000-0003-4656-5659"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Bong-Soo Sohn","raw_affiliation_strings":["Computer Science Department, Chung-Ang University, Seoul, South Korea","Computer Science Department, Chung-Ang University, Seoul, Korea"],"raw_orcid":"https://orcid.org/0000-0003-4656-5659","affiliations":[{"raw_affiliation_string":"Computer Science Department, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Computer Science Department, Chung-Ang University, Seoul, Korea","institution_ids":["https://openalex.org/I67900169"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022648850","display_name":"Simon Korman","orcid":null},"institutions":[{"id":"https://openalex.org/I91203450","display_name":"University of Haifa","ror":"https://ror.org/02f009v59","country_code":"IL","type":"education","lineage":["https://openalex.org/I91203450"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Simon Korman","raw_affiliation_strings":["Department of Computer Science, University of Haifa, Haifa, Israel"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Haifa, Haifa, Israel","institution_ids":["https://openalex.org/I91203450"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065943331","display_name":"Byung\u2010Woo Hong","orcid":"https://orcid.org/0000-0003-2752-3939"},"institutions":[{"id":"https://openalex.org/I67900169","display_name":"Chung-Ang University","ror":"https://ror.org/01r024a98","country_code":"KR","type":"education","lineage":["https://openalex.org/I67900169"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Byung-Woo Hong","raw_affiliation_strings":["Artificial Intelligence Department, Chung-Ang University, Seoul, South Korea","Computer Science Department, Chung-Ang University, Seoul, Korea"],"raw_orcid":"https://orcid.org/0000-0003-2752-3939","affiliations":[{"raw_affiliation_string":"Artificial Intelligence Department, Chung-Ang University, Seoul, South Korea","institution_ids":["https://openalex.org/I67900169"]},{"raw_affiliation_string":"Computer Science Department, Chung-Ang University, Seoul, Korea","institution_ids":["https://openalex.org/I67900169"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.3653,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.8549937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"13","issue":null,"first_page":"113258","last_page":"113273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11205","display_name":"Numerical methods in inverse problems","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/2610","display_name":"Mathematical Physics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9334999918937683,"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/T12100","display_name":"Advanced Mathematical Modeling in Engineering","score":0.9200000166893005,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/regularization","display_name":"Regularization (linguistics)","score":0.632049560546875},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6045432090759277},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4421384632587433},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4379284381866455},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.412350594997406},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.09288233518600464}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.632049560546875},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6045432090759277},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4421384632587433},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4379284381866455},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.412350594997406},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.09288233518600464}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2025.3582756","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3582756","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:13170482bc8d4e828c95c2aac97c3cb3","is_oa":true,"landing_page_url":"https://doaj.org/article/13170482bc8d4e828c95c2aac97c3cb3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 13, Pp 113258-113273 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2025.3582756","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2025.3582756","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1882192421","display_name":null,"funder_award_id":"IITP-RS-2021-II211341","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"},{"id":"https://openalex.org/G6053833429","display_name":null,"funder_award_id":"NRF-RS-2023-00251366","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"},{"id":"https://openalex.org/G7323469946","display_name":null,"funder_award_id":"IITP-2021-0-01341","funder_id":"https://openalex.org/F4320328359","funder_display_name":"Ministry of Science and ICT, South Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"},{"id":"https://openalex.org/F4320328359","display_name":"Ministry of Science and ICT, South Korea","ror":"https://ror.org/01wpjm123"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W2112796928","https://openalex.org/W2533598788","https://openalex.org/W2794022343","https://openalex.org/W2954360087","https://openalex.org/W2954996726","https://openalex.org/W2963108767","https://openalex.org/W2965141076","https://openalex.org/W3008062779","https://openalex.org/W3034600949","https://openalex.org/W3080580366","https://openalex.org/W3174807077","https://openalex.org/W4221165315","https://openalex.org/W4312742492","https://openalex.org/W4312933868","https://openalex.org/W4380884624","https://openalex.org/W4381187558","https://openalex.org/W4382240059","https://openalex.org/W4386071814","https://openalex.org/W4386075657","https://openalex.org/W4386076098","https://openalex.org/W4386621056","https://openalex.org/W4386688978","https://openalex.org/W4389904042","https://openalex.org/W4390872719","https://openalex.org/W4391046504","https://openalex.org/W4402716178","https://openalex.org/W4402716318","https://openalex.org/W4402727082","https://openalex.org/W4402727738","https://openalex.org/W4402727835","https://openalex.org/W4402733583","https://openalex.org/W4402753872","https://openalex.org/W4402754224","https://openalex.org/W4402780116","https://openalex.org/W4402816839","https://openalex.org/W6625168331","https://openalex.org/W6679045638","https://openalex.org/W6684191040","https://openalex.org/W6718379498","https://openalex.org/W6743428213","https://openalex.org/W6747218270","https://openalex.org/W6747899497","https://openalex.org/W6757817989","https://openalex.org/W6758184449","https://openalex.org/W6765775151","https://openalex.org/W6765779288","https://openalex.org/W6776700526","https://openalex.org/W6779093361","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6786375611","https://openalex.org/W6790605485","https://openalex.org/W6795288823","https://openalex.org/W6796585546","https://openalex.org/W6809589807","https://openalex.org/W6840815571","https://openalex.org/W6849141701","https://openalex.org/W6852213543","https://openalex.org/W6853584353","https://openalex.org/W6853622345","https://openalex.org/W6857036795"],"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":{"Diffusion":[0],"models":[1],"are":[2,16],"a":[3,53,96],"powerful":[4],"class":[5],"of":[6,131],"techniques":[7],"in":[8,45,99,140],"ML":[9],"for":[10,61],"generating":[11],"realistic":[12],"data,":[13],"but":[14],"they":[15],"highly":[17],"prone":[18],"to":[19],"overfitting,":[20],"especially":[21],"with":[22,83,106,142],"limited":[23,143],"training":[24,62,141],"data.":[25,85,144],"While":[26],"data":[27,74],"augmentation":[28],"such":[29],"as":[30,109],"image":[31,107,132],"rotation":[32,108],"can":[33],"mitigate":[34],"this":[35,49],"issue,":[36],"it":[37],"often":[38],"causes":[39],"leakage,":[40],"where":[41],"augmented":[42],"content":[43],"appears":[44],"generated":[46],"samples.":[47],"In":[48,134],"paper,":[50],"we":[51],"propose":[52],"novel":[54],"regularization":[55,91,129],"framework,":[56],"called":[57],"shifted":[58],"data-augmentation":[59],"(SDA),":[60],"unconditional":[63],"diffusion":[64,70,101],"models.":[65],"SDA":[66,105,125,136],"introduces":[67],"an":[68],"auxiliary":[69],"path":[71,82],"using":[72],"transformed":[73],"and":[75,113,120],"the":[76,80,100,128],"noise-shift":[77],"technique":[78],"alongside":[79],"standard":[81],"original":[84],"This":[86],"dual-path":[87],"structure":[88],"enables":[89],"effective":[90],"while":[92],"suppressing":[93],"leakage":[94],"through":[95],"trajectory":[97],"shift":[98],"process.":[102],"We":[103,116],"implement":[104],"its":[110],"most":[111],"basic":[112],"interpretable":[114],"configuration.":[115],"also":[117],"conduct":[118],"synthetic":[119],"empirical":[121],"analyses":[122],"demonstrating":[123],"that":[124],"effectively":[126],"leverages":[127],"benefit":[130],"rotation.":[133],"particular,":[135],"yielded":[137],"notable":[138],"performance":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}