{"id":"https://openalex.org/W2977729751","doi":"https://doi.org/10.1109/ijcnn.2019.8851926","title":"Boosted GAN with Semantically Interpretable Information for Image Inpainting","display_name":"Boosted GAN with Semantically Interpretable Information for Image Inpainting","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2977729751","doi":"https://doi.org/10.1109/ijcnn.2019.8851926","mag":"2977729751"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2019.8851926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5100413576","display_name":"Ang Li","orcid":"https://orcid.org/0000-0001-7149-3250"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Ang Li","raw_affiliation_strings":["The University of Melbourne"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022290876","display_name":"Jianzhong Qi","orcid":"https://orcid.org/0000-0001-6501-9050"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jianzhong Qi","raw_affiliation_strings":["The University of Melbourne"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100422092","display_name":"Rui Zhang","orcid":"https://orcid.org/0000-0002-8132-6250"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Rui Zhang","raw_affiliation_strings":["The University of Melbourne"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069895484","display_name":"Kotagiri Ramamohanarao","orcid":"https://orcid.org/0000-0003-3304-9268"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Ramamohanarao Kotagiri","raw_affiliation_strings":["The University of Melbourne"],"affiliations":[{"raw_affiliation_string":"The University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100413576"],"corresponding_institution_ids":["https://openalex.org/I165779595"],"apc_list":null,"apc_paid":null,"fwci":1.1135,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.8232729,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"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":0.9995999932289124,"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":0.9995999932289124,"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":0.995199978351593,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9807999730110168,"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/inpainting","display_name":"Inpainting","score":0.9793300628662109},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.8321032524108887},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7584779262542725},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7328658103942871},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6584535241127014},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6571161150932312},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5625637769699097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.548599123954773},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49377211928367615},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4932686686515808},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4679868221282959}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.9793300628662109},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8321032524108887},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7584779262542725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7328658103942871},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6584535241127014},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6571161150932312},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5625637769699097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.548599123954773},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49377211928367615},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4932686686515808},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4679868221282959},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2019.8851926","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2019.8851926","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":57,"referenced_works":["https://openalex.org/W1567302070","https://openalex.org/W1686810756","https://openalex.org/W1796263212","https://openalex.org/W1834627138","https://openalex.org/W1903029394","https://openalex.org/W1993120651","https://openalex.org/W1999360130","https://openalex.org/W2017814585","https://openalex.org/W2093212899","https://openalex.org/W2099471712","https://openalex.org/W2116013899","https://openalex.org/W2123031198","https://openalex.org/W2123229215","https://openalex.org/W2125389028","https://openalex.org/W2141362318","https://openalex.org/W2148809531","https://openalex.org/W2163879248","https://openalex.org/W2405756170","https://openalex.org/W2410641892","https://openalex.org/W2412782625","https://openalex.org/W2549365021","https://openalex.org/W2557414982","https://openalex.org/W2560023338","https://openalex.org/W2630837129","https://openalex.org/W2732026016","https://openalex.org/W2737258237","https://openalex.org/W2738588019","https://openalex.org/W2798365772","https://openalex.org/W2896434438","https://openalex.org/W2903396356","https://openalex.org/W2962760235","https://openalex.org/W2963020325","https://openalex.org/W2963073614","https://openalex.org/W2963300078","https://openalex.org/W2963420272","https://openalex.org/W2963567641","https://openalex.org/W2963684088","https://openalex.org/W2963745697","https://openalex.org/W2963800363","https://openalex.org/W2963917315","https://openalex.org/W2964024144","https://openalex.org/W2964309882","https://openalex.org/W3043547428","https://openalex.org/W3106359998","https://openalex.org/W4294643831","https://openalex.org/W4320013936","https://openalex.org/W6637373629","https://openalex.org/W6678815747","https://openalex.org/W6685352114","https://openalex.org/W6687500345","https://openalex.org/W6713645886","https://openalex.org/W6720932270","https://openalex.org/W6739696289","https://openalex.org/W6740934225","https://openalex.org/W6745560452","https://openalex.org/W6748481559","https://openalex.org/W6756633790"],"related_works":["https://openalex.org/W2380775572","https://openalex.org/W2213520135","https://openalex.org/W2244018504","https://openalex.org/W4242046654","https://openalex.org/W3174923100","https://openalex.org/W3134074939","https://openalex.org/W2117562399","https://openalex.org/W4298074124","https://openalex.org/W3214306048","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Image":[0],"inpainting":[1,24,69,112,129,134,141,163],"aims":[2],"at":[3],"restoring":[4],"missing":[5,80,104],"regions":[6],"of":[7,48,67,100,132,155],"corrupted":[8],"images,":[9],"which":[10],"has":[11],"many":[12,75],"applications":[13],"such":[14],"as":[15,95],"image":[16,44,46,128],"restoration":[17],"and":[18,36,97,136,152,158,190,210,213],"object":[19],"removal.":[20],"However,":[21],"current":[22,52],"GAN-based":[23,68],"models":[25,53,72],"fail":[26],"to":[27,64,148,165],"explicitly":[28],"consider":[29],"the":[30,65,111,150,162,194,216],"semantic":[31],"consistency":[32,192,206],"between":[33],"restored":[34],"images":[35,102,157],"original":[37,195],"images.":[38,196],"For":[39],"example,":[40],"given":[41,78],"a":[42,58,79,120,137,174],"male":[43],"with":[45,57,123,193],"region":[47],"one":[49],"eye":[50],"missing,":[51],"may":[54],"restore":[55],"it":[56],"female":[59],"eye.":[60],"This":[61],"is":[62,89],"due":[63],"ambiguity":[66],"models:":[70],"these":[71],"can":[73,106,178,204],"generate":[74],"possible":[76],"restorations":[77],"region.":[81],"To":[82],"address":[83],"this":[84,116],"limitation,":[85],"our":[86,201],"key":[87],"insight":[88],"that":[90,130,177,200],"semantically":[91,124],"interpretable":[92,125],"information":[93,126,154],"(such":[94],"attribute":[96,151,189,209],"segmentation":[98,153,191,211],"information)":[99],"input":[101,156],"(with":[103],"regions)":[105],"provide":[107,166],"essential":[108],"guidance":[109],"for":[110,127],"process.":[113],"Based":[114],"on":[115,183,188,207],"insight,":[117],"we":[118],"propose":[119],"boosted":[121],"GAN":[122],"consists":[131],"an":[133],"network":[135,142,172],"discriminative":[138,171],"network.":[139],"The":[140,170],"utilizes":[143],"two":[144],"auxiliary":[145],"pretrained":[146],"networks":[147],"discover":[149],"incorporates":[159],"them":[160],"into":[161],"process":[164],"explicit":[167],"semantic-level":[168],"guidance.":[169],"adopts":[173],"multi-level":[175],"design":[176],"enforce":[179],"regularizations":[180],"not":[181],"only":[182],"overall":[184],"realness":[185],"but":[186],"also":[187],"Experimental":[197],"results":[198],"show":[199],"proposed":[202],"model":[203],"preserve":[205],"both":[208],"level,":[212],"significantly":[214],"outperforms":[215],"state-of-the-art":[217],"models.":[218]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
