{"id":"https://openalex.org/W7105647271","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228154","title":"Analyzing Face Image Inpainting with Attribute-Driven Generative Network","display_name":"Analyzing Face Image Inpainting with Attribute-Driven Generative Network","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W7105647271","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228154"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228154","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":null,"display_name":"Rishabh Shukla","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127441","display_name":"Indian Institute of Technology Jammu","ror":"https://ror.org/02f0vsw63","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210127441"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Rishabh Shukla","raw_affiliation_strings":["IIT,Jammu,India"],"affiliations":[{"raw_affiliation_string":"IIT,Jammu,India","institution_ids":["https://openalex.org/I4210127441"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Harkeerat Kaur","orcid":null},"institutions":[{"id":"https://openalex.org/I4210127441","display_name":"Indian Institute of Technology Jammu","ror":"https://ror.org/02f0vsw63","country_code":"IN","type":"education","lineage":["https://openalex.org/I4210127441"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Harkeerat Kaur","raw_affiliation_strings":["IIT,Jammu,India"],"affiliations":[{"raw_affiliation_string":"IIT,Jammu,India","institution_ids":["https://openalex.org/I4210127441"]}]},{"author_position":"last","author":{"id":null,"display_name":"Isao Echizen","orcid":null},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Isao Echizen","raw_affiliation_strings":["National Institute of Informatics,Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics,Japan","institution_ids":["https://openalex.org/I184597095"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210127441"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.57722448,"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":"9"},"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":0.9648000001907349,"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":0.9648000001907349,"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/T11448","display_name":"Face recognition and analysis","score":0.024900000542402267,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.0006000000284984708,"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/discriminator","display_name":"Discriminator","score":0.8406999707221985},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.8325999975204468},{"id":"https://openalex.org/keywords/inpainting","display_name":"Inpainting","score":0.7372000217437744},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6579999923706055},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6395999789237976},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6018999814987183},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.5091000199317932},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5009999871253967},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.4830000102519989}],"concepts":[{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.8406999707221985},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.8325999975204468},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7689999938011169},{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.7372000217437744},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7332000136375427},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6579999923706055},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6395999789237976},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6018999814987183},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5091000199317932},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5009999871253967},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.43540000915527344},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4165000021457672},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40310001373291016},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.36070001125335693},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3463999927043915},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34220001101493835},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.32839998602867126},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.29019999504089355},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.2856000065803528},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.28529998660087585},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.2800000011920929},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27090001106262207},{"id":"https://openalex.org/C75294576","wikidata":"https://www.wikidata.org/wiki/Q5165192","display_name":"Contextual image classification","level":3,"score":0.26260000467300415},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.26249998807907104},{"id":"https://openalex.org/C2911011789","wikidata":"https://www.wikidata.org/wiki/Q130741","display_name":"Hallucinating","level":2,"score":0.2567000091075897},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.25609999895095825}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228154","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228154","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":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.721467912197113}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W1993120651","https://openalex.org/W2064076387","https://openalex.org/W2133665775","https://openalex.org/W2611104282","https://openalex.org/W2738588019","https://openalex.org/W2798365772","https://openalex.org/W2890546957","https://openalex.org/W2962770929","https://openalex.org/W2962793481","https://openalex.org/W2962974533","https://openalex.org/W2963073614","https://openalex.org/W2963420272","https://openalex.org/W2963521568","https://openalex.org/W2963767194","https://openalex.org/W2981408470","https://openalex.org/W2982763192","https://openalex.org/W2985068832","https://openalex.org/W2985764327","https://openalex.org/W2997669187","https://openalex.org/W3026885507","https://openalex.org/W3035574324","https://openalex.org/W3043547428","https://openalex.org/W3102061158","https://openalex.org/W3126979782","https://openalex.org/W3171874329","https://openalex.org/W3173102319","https://openalex.org/W3176913662","https://openalex.org/W3177221875","https://openalex.org/W3203538104","https://openalex.org/W4240726888","https://openalex.org/W4285981784","https://openalex.org/W4294225111","https://openalex.org/W4310443798","https://openalex.org/W4312933868","https://openalex.org/W4360995365","https://openalex.org/W4386072096","https://openalex.org/W4386076425","https://openalex.org/W4391306719","https://openalex.org/W4394625855","https://openalex.org/W4404838560"],"related_works":[],"abstract_inverted_index":{"These":[0,68],"days,":[1],"deep":[2],"learning":[3],"has":[4,16,60],"gained":[5],"popularity":[6],"as":[7,57,62,94,143],"a":[8,26,33,63,109,155],"widely":[9],"used":[10],"technique":[11,74],"for":[12,66,120],"image":[13,81,122],"inpainting.":[14,67,123],"It":[15,138],"the":[17,23,48,58,71,131,135,148,161,169,174,185,190],"ability":[18],"to":[19,75,129,146,172],"not":[20],"only":[21],"recover":[22],"texture":[24],"of":[25,45,50,115,134,192],"picture":[27],"and":[28,79,83,97,117,196,199],"extract":[29],"abstract":[30],"information":[31],"at":[32],"high":[34],"level":[35],"but":[36],"also":[37],"restore":[38],"semantic":[39],"representations":[40],"like":[41],"human":[42],"faces.":[43],"Out":[44],"these":[46,105],"methods,":[47],"use":[49],"generative":[51],"adversarial":[52],"networks":[53],"(GANs)":[54,89],"with":[55],"autoencoder":[56],"generator":[59,136,149],"emerged":[61],"potential":[64],"paradigm":[65],"models":[69],"utilize":[70,118],"end-to-end":[72],"inpainting":[73],"produce":[76],"visually":[77,201],"coherent":[78],"distinct":[80],"structures":[82],"textures.":[84],"Nevertheless,":[85],"Generative":[86],"Adversarial":[87],"Networks":[88],"frequently":[90],"encounter":[91],"issues":[92],"such":[93],"gradient":[95],"vanishing":[96],"model":[98],"collapse":[99],"when":[100],"being":[101],"trained.":[102],"To":[103],"address":[104],"challenges,":[106],"we":[107],"introduce":[108],"novel":[110],"approach":[111],"called":[112],"attribute-driven":[113],"training":[114,132,141,144],"GAN":[116],"it":[119,153],"face":[121],"The":[124,164],"proposed":[125,186],"work":[126,187],"utilizes":[127],"attributes":[128],"stabilize":[130],"process":[133],"network.":[137],"employs":[139],"different":[140],"keys":[142],"objectives":[145],"update":[147],"network\u2019s":[150],"parameters.":[151],"Additionally,":[152],"uses":[154],"classification":[156],"module,":[157],"which":[158],"helps":[159],"determine":[160],"bestfit":[162],"key.":[163],"discriminator":[165],"is":[166],"aided":[167],"by":[168],"loss":[170],"functions":[171],"critique":[173],"generated":[175],"image.":[176],"Experiments":[177],"conducted":[178],"on":[179],"CelebA":[180],"[25]":[181],"datasets":[182],"demonstrate":[183],"that":[184],"effectively":[188],"addresses":[189],"issue":[191],"artifacts,":[193],"accomplishes":[194],"consistent":[195],"efficient":[197],"training,":[198],"produces":[200],"plausible":[202],"images.":[203]},"counts_by_year":[],"updated_date":"2025-11-15T23:13:30.683059","created_date":"2025-11-14T00:00:00"}