{"id":"https://openalex.org/W4409985869","doi":"https://doi.org/10.1109/tmm.2025.3565978","title":"MGDefect: A Mask-Guided High-Quality Defect Image Generation Method for Improving Defect Inspection","display_name":"MGDefect: A Mask-Guided High-Quality Defect Image Generation Method for Improving Defect Inspection","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4409985869","doi":"https://doi.org/10.1109/tmm.2025.3565978"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2025.3565978","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3565978","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Transactions on Multimedia","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/A5060665015","display_name":"Xiaoheng Jiang","orcid":"https://orcid.org/0000-0002-5770-0417"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaoheng Jiang","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425082","display_name":"Yingjie Li","orcid":"https://orcid.org/0009-0004-1499-4613"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingjie Li","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101527301","display_name":"Feng Yan","orcid":"https://orcid.org/0000-0002-2683-8878"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Yan","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015452096","display_name":"Yang Lu","orcid":"https://orcid.org/0000-0002-2564-1993"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Lu","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022636178","display_name":"Changsheng Xu","orcid":"https://orcid.org/0000-0001-8343-9665"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"funder","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changsheng Xu","raw_affiliation_strings":["State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5081346568","display_name":"Mingliang Xu","orcid":"https://orcid.org/0000-0002-6885-3451"},"institutions":[{"id":"https://openalex.org/I38877650","display_name":"Zhengzhou University","ror":"https://ror.org/04ypx8c21","country_code":"CN","type":"education","lineage":["https://openalex.org/I38877650"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingliang Xu","raw_affiliation_strings":["School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou, China","institution_ids":["https://openalex.org/I38877650"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5060665015"],"corresponding_institution_ids":["https://openalex.org/I38877650"],"apc_list":null,"apc_paid":null,"fwci":1.3199,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.80878499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12169","display_name":"Non-Destructive Testing Techniques","score":0.9750999808311462,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11338","display_name":"Advancements in Photolithography Techniques","score":0.9495999813079834,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7423551678657532},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5389099717140198},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5323370695114136},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.47906693816185},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.44698193669319153},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3441508710384369},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32046234607696533}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7423551678657532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5389099717140198},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5323370695114136},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.47906693816185},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.44698193669319153},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3441508710384369},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32046234607696533},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2025.3565978","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2025.3565978","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W2779427294","https://openalex.org/W2775347418","https://openalex.org/W2625805835","https://openalex.org/W2079911747","https://openalex.org/W3116076068","https://openalex.org/W3003936178","https://openalex.org/W2145652935","https://openalex.org/W2563206327","https://openalex.org/W2069885731"],"abstract_inverted_index":{"Deep":[0],"learning":[1],"based":[2],"defect":[3,46,57,65,87,177,191,224,231],"inspection":[4,232],"methods":[5],"have":[6],"achieved":[7],"promising":[8,214],"performance,":[9],"which":[10,83,185],"usually":[11],"relies":[12],"on":[13,174,189,199,250,254,259,271],"a":[14,53,75,104,111],"large":[15,54],"number":[16],"of":[17,56,61,97,103,230,248],"well-labeled":[18],"training":[19,49],"samples.":[20,47,196],"However,":[21,48],"it":[22],"requires":[23,52],"much":[24],"effort":[25],"to":[26,44,145,163],"obtain":[27],"enough":[28],"annotated":[29],"samples":[30,66,88,192,225],"especially":[31],"pixel-level":[32,68,90],"annotations":[33,91],"in":[34,182],"practical":[35],"production.":[36],"Generative":[37],"adversarial":[38],"networks":[39],"(GANs)":[40],"can":[41,84],"be":[42],"utilized":[43],"generate":[45,64,85,146,164],"GANs":[50],"typically":[51],"amount":[55],"data":[58],"and":[59,92,110,125,130,140,148,157,179,193,205,236,257,269],"most":[60],"them":[62],"cannot":[63],"with":[67,89,121,167,217],"annotations.":[69],"In":[70],"this":[71],"paper,":[72],"we":[73],"present":[74],"Mask-Guided":[76,105],"Defect":[77,106,112],"image":[78,141],"generation":[79],"method,":[80],"called":[81],"MGDefect,":[82],"high-quality":[86],"effectively":[93],"improves":[94,264],"the":[95,131,137,168,200,222,228,278],"performance":[96,229],"downstream":[98],"tasks.":[99],"Specifically,":[100,238],"MGDefect":[101],"consists":[102],"Generation":[107],"GAN":[108,114],"(MGDG-GAN)":[109],"Mask":[113],"(DM-GAN).":[115],"MGDG-GAN":[116,171],"generates":[117],"images":[118],"containing":[119],"defects":[120,135],"specific":[122],"locations,":[123],"shapes,":[124],"sizes":[126],"via":[127],"mask":[128],"guidance":[129],"dual":[132,159],"discrimination":[133,160],"for":[134,151,161],"at":[136],"region":[138],"level":[139],"level.":[142],"DM-GAN":[143,180],"aims":[144],"diverse":[147],"rational":[149],"masks":[150,162,166],"MGDG-GAN.":[152],"It":[153],"also":[154],"adopts":[155],"region-level":[156],"image-level":[158],"compatible":[165],"target":[169],"objects.":[170],"mainly":[172],"focuses":[173],"generating":[175,183],"local":[176],"regions":[178],"specializes":[181],"masks,":[184],"are":[186],"both":[187],"trained":[188],"limited":[190],"abundant":[194],"normal":[195],"Experiments":[197],"conducted":[198],"MVTec":[201,251],"AD,":[202,252],"DAGM":[203,255],"2007,":[204,256],"KolektorSDD2":[206],"benchmark":[207],"datasets":[208],"demonstrate":[209],"that":[210],"our":[211,239,262],"method":[212,240,263],"achieves":[213,241],"results":[215],"compared":[216],"other":[218],"state-of-the-art":[219],"approaches.":[220],"Meanwhile,":[221],"generated":[223],"significantly":[226],"improve":[227],"tasks":[233],"including":[234],"classification":[235],"segmentation.":[237],"KID<inline-formula":[242],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[243],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[244],"notation=\"LaTeX\">$\\times":[245],"10^{3}$</tex-math></inline-formula>/IS":[246],"scores":[247],"48.35/2.27":[249],"15.37/2.44":[253],"19.70/2.01":[258],"KolektorSDD2.":[260],"Furthermore,":[261],"mIoU":[265],"by":[266],"10.59%,":[267],"2.20%,":[268],"2.17%":[270],"these":[272],"datasets,":[273],"respectively,":[274],"using":[275],"U-Net":[276],"as":[277],"segmentation":[279],"model.":[280]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}