{"id":"https://openalex.org/W4416251569","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228158","title":"Enhancing Synthetic Image Realism with Controlled Diffusion Models","display_name":"Enhancing Synthetic Image Realism with Controlled Diffusion Models","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251569","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228158"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228158","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228158","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","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/A5094209704","display_name":"Iqra Nosheen","orcid":null},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":true,"raw_author_name":"Iqra Nosheen","raw_affiliation_strings":["School of Computer Science, University of Galway,Galway,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Galway,Galway,Ireland","institution_ids":["https://openalex.org/I188760350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043073773","display_name":"Muhammad Ali Farooq","orcid":"https://orcid.org/0000-0003-4116-8021"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Muhammad Ali Farooq","raw_affiliation_strings":["School of Engineering, University of Galway,Galway,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Galway,Galway,Ireland","institution_ids":["https://openalex.org/I188760350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066217549","display_name":"Peter Corcoran","orcid":"https://orcid.org/0000-0003-1670-4793"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Peter Corcoran","raw_affiliation_strings":["School of Engineering, University of Galway,Galway,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Engineering, University of Galway,Galway,Ireland","institution_ids":["https://openalex.org/I188760350"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108170023","display_name":"Cathy Ennis","orcid":"https://orcid.org/0009-0001-0353-1179"},"institutions":[{"id":"https://openalex.org/I157286207","display_name":"National University of Ireland, Maynooth","ror":"https://ror.org/048nfjm95","country_code":"IE","type":"education","lineage":["https://openalex.org/I157286207"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Cathy Ennis","raw_affiliation_strings":["School of Computer Science, Maynooth University,Dublin,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Maynooth University,Dublin,Ireland","institution_ids":["https://openalex.org/I157286207"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006608063","display_name":"Michael G. Madden","orcid":"https://orcid.org/0000-0002-4443-7285"},"institutions":[{"id":"https://openalex.org/I188760350","display_name":"Ollscoil na Gaillimhe \u2013 University of Galway","ror":"https://ror.org/03bea9k73","country_code":"IE","type":"education","lineage":["https://openalex.org/I188760350"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Michael G. Madden","raw_affiliation_strings":["School of Computer Science, University of Galway,Galway,Ireland"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, University of Galway,Galway,Ireland","institution_ids":["https://openalex.org/I188760350"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5094209704"],"corresponding_institution_ids":["https://openalex.org/I188760350"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37476582,"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":"8"},"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":0.620199978351593,"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":0.620199978351593,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.16850000619888306,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.0502999983727932,"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/synthetic-data","display_name":"Synthetic data","score":0.7822999954223633},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5730000138282776},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5041000247001648},{"id":"https://openalex.org/keywords/usability","display_name":"Usability","score":0.4505000114440918},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.37470000982284546},{"id":"https://openalex.org/keywords/experimental-data","display_name":"Experimental data","score":0.3621000051498413},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.35370001196861267},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.35109999775886536}],"concepts":[{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.7822999954223633},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694599986076355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6219000220298767},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5730000138282776},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5041000247001648},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4927000105381012},{"id":"https://openalex.org/C170130773","wikidata":"https://www.wikidata.org/wiki/Q216378","display_name":"Usability","level":2,"score":0.4505000114440918},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.37470000982284546},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.3621000051498413},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.35370001196861267},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.3508000075817108},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3352000117301941},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3310999870300293},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.31769999861717224},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2962999939918518},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.29159998893737793},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.29159998893737793},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.28209999203681946},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228158","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228158","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W2150066425","https://openalex.org/W2954360087","https://openalex.org/W2962804601","https://openalex.org/W3082846761","https://openalex.org/W3108316907","https://openalex.org/W3173126908","https://openalex.org/W3207649350","https://openalex.org/W3210822187","https://openalex.org/W4293231989","https://openalex.org/W4320487136","https://openalex.org/W4385804983","https://openalex.org/W4386072096","https://openalex.org/W4387194140","https://openalex.org/W4390873054","https://openalex.org/W4390873442","https://openalex.org/W4392901999","https://openalex.org/W4393160557","https://openalex.org/W4394593113","https://openalex.org/W4400644945","https://openalex.org/W4402753671","https://openalex.org/W4402916536","https://openalex.org/W4403049104","https://openalex.org/W4405801753","https://openalex.org/W4407874056","https://openalex.org/W4410540154"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1,187,220],"work,":[2,213],"we":[3,99],"present":[4],"an":[5],"innovative":[6],"approach":[7,124,199],"utilizing":[8,67],"ControlNet-based":[9],"diffusion":[10],"models":[11,49,217],"along":[12,214],"with":[13,87,215],"upscaling":[14],"capabilities":[15],"for":[16,54,142],"domain":[17,34,90,209],"adaptation":[18],"and":[19,40,78,98,119,157,159,171,179,193,208],"quality":[20],"refinement":[21],"of":[22,46,62,116,168,186,195],"3D":[23,135],"modelled":[24,136],"synthetic":[25,39,52,84,137,196],"datasets,":[26],"focusing":[27],"on":[28,51,125,163],"autonomous":[29,143],"vehicle":[30],"applications.":[31],"A":[32],"significant":[33],"gap":[35],"often":[36],"exists":[37],"between":[38],"real-world":[41,55],"data,":[42],"hindering":[43],"the":[44,60,88,95,114,123,130,184,191],"applicability":[45],"deep":[47],"learning":[48,166],"trained":[50],"data":[53,85,148,206],"scenarios.":[56],"Our":[57,198],"methodology":[58],"leverages":[59],"strengths":[61],"Controlled":[63],"Augmentation":[64],"by":[65],"simultaneously":[66],"multiple":[68],"ControlNet":[69,216],"signals,":[70],"including":[71,154],"edge":[72],"detection,":[73],"depth":[74],"information,":[75],"segmentation":[76],"maps,":[77],"tile":[79],"resampling.":[80],"To":[81],"improve":[82,111],"how":[83],"aligns":[86],"desired":[89,117],"specifications,":[91],"these":[92],"signals":[93],"guide":[94],"generative":[96],"process,":[97],"also":[100,161],"incorporate":[101],"text-guided":[102],"prompts":[103],"extracted":[104],"via":[105],"Large":[106],"Language":[107],"Models":[108],"(LLMs),":[109],"to":[110,175,201],"control":[112],"over":[113],"synthesis":[115,207],"features":[118],"attributes.":[120],"We":[121],"test":[122],"diverse":[126],"environmental":[127],"conditions":[128],"from":[129],"VKITTI":[131],"dataset,":[132],"a":[133],"well-known":[134],"dataset":[138],"generated":[139],"in":[140,189,219],"Unity":[141],"driving":[144],"research.":[145],"The":[146,211],"refined":[147],"is":[149,160,222],"validated":[150],"using":[151,173],"quantitative":[152],"metrics":[153],"FID,":[155],"SSIM,":[156],"LPIPS,":[158],"evaluated":[162],"downstream":[164],"machine":[165],"tasks":[167],"object":[169],"detection":[170],"classification,":[172],"YOLO-v8":[174],"ensure":[176],"its":[177],"utility":[178],"effectiveness.":[180],"Experimental":[181],"analysis":[182],"demonstrates":[183],"effectiveness":[185],"method":[188],"improving":[190],"realism":[192],"usability":[194],"data.":[197],"contributes":[200],"fields":[202],"that":[203],"require":[204],"high-quality":[205],"adaptation.":[210],"experimental":[212],"used":[218],"project":[221],"available":[223],"online.<sup":[224],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[225],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[226]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-11-14T00:00:00"}
