{"id":"https://openalex.org/W3089766305","doi":"https://doi.org/10.1109/icip40778.2020.9191340","title":"Where Is The Fake? Patch-Wise Supervised Gans For Texture Inpainting","display_name":"Where Is The Fake? Patch-Wise Supervised Gans For Texture Inpainting","publication_year":2020,"publication_date":"2020-09-30","ids":{"openalex":"https://openalex.org/W3089766305","doi":"https://doi.org/10.1109/icip40778.2020.9191340","mag":"3089766305"},"language":"en","primary_location":{"id":"doi:10.1109/icip40778.2020.9191340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5033912951","display_name":"Ahmed Saad","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmed Ben Saad","raw_affiliation_strings":["CMLA, ENS Paris-Saclay"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CMLA, ENS Paris-Saclay","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052965014","display_name":"Youssef Tamaazousti","orcid":"https://orcid.org/0000-0001-7703-9147"},"institutions":[{"id":"https://openalex.org/I154100212","display_name":"Schlumberger (British Virgin Islands)","ror":"https://ror.org/01ydfc370","country_code":"VG","type":"company","lineage":["https://openalex.org/I154100212","https://openalex.org/I4210092184"]}],"countries":["VG"],"is_corresponding":false,"raw_author_name":"Youssef Tamaazousti","raw_affiliation_strings":["Schlumberger AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Schlumberger AI Lab","institution_ids":["https://openalex.org/I154100212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023246336","display_name":"Josselin Kherroubi","orcid":null},"institutions":[{"id":"https://openalex.org/I154100212","display_name":"Schlumberger (British Virgin Islands)","ror":"https://ror.org/01ydfc370","country_code":"VG","type":"company","lineage":["https://openalex.org/I154100212","https://openalex.org/I4210092184"]}],"countries":["VG"],"is_corresponding":false,"raw_author_name":"Josselin Kherroubi","raw_affiliation_strings":["Schlumberger AI Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Schlumberger AI Lab","institution_ids":["https://openalex.org/I154100212"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5051364835","display_name":"Alexis He","orcid":null},"institutions":[{"id":"https://openalex.org/I154100212","display_name":"Schlumberger (British Virgin Islands)","ror":"https://ror.org/01ydfc370","country_code":"VG","type":"company","lineage":["https://openalex.org/I154100212","https://openalex.org/I4210092184"]}],"countries":["VG"],"is_corresponding":false,"raw_author_name":"Alexis He","raw_affiliation_strings":["Etudes et Productions Schlumberger"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Etudes et Productions Schlumberger","institution_ids":["https://openalex.org/I154100212"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"568","last_page":"572"},"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":0.9997000098228455,"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":0.9997000098228455,"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":0.9904000163078308,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9815000295639038,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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":0.9653854370117188},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.7780505418777466},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7573658227920532},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7541929483413696},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6847243309020996},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6177414655685425},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6034554243087769},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5778862237930298},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.5546813011169434},{"id":"https://openalex.org/keywords/texture-synthesis","display_name":"Texture synthesis","score":0.5291735529899597},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5168595910072327},{"id":"https://openalex.org/keywords/image-texture","display_name":"Image texture","score":0.4247952699661255},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.20854702591896057}],"concepts":[{"id":"https://openalex.org/C11727466","wikidata":"https://www.wikidata.org/wiki/Q1628157","display_name":"Inpainting","level":3,"score":0.9653854370117188},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.7780505418777466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7573658227920532},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7541929483413696},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6847243309020996},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6177414655685425},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6034554243087769},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5778862237930298},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.5546813011169434},{"id":"https://openalex.org/C50494287","wikidata":"https://www.wikidata.org/wiki/Q658467","display_name":"Texture synthesis","level":5,"score":0.5291735529899597},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5168595910072327},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.4247952699661255},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.20854702591896057},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip40778.2020.9191340","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip40778.2020.9191340","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7099999785423279,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W124696327","https://openalex.org/W1901129140","https://openalex.org/W2047643928","https://openalex.org/W2070604790","https://openalex.org/W2099471712","https://openalex.org/W2105038642","https://openalex.org/W2123045220","https://openalex.org/W2194775991","https://openalex.org/W2494091040","https://openalex.org/W2645993785","https://openalex.org/W2738588019","https://openalex.org/W2792263949","https://openalex.org/W2897598705","https://openalex.org/W2953030256","https://openalex.org/W2962785568","https://openalex.org/W2963073614","https://openalex.org/W2963104543","https://openalex.org/W2963382180","https://openalex.org/W2963420272","https://openalex.org/W2963840672","https://openalex.org/W2997095758","https://openalex.org/W3001217199","https://openalex.org/W4320013936","https://openalex.org/W6605030200","https://openalex.org/W6639824700","https://openalex.org/W6677995690","https://openalex.org/W6696085341","https://openalex.org/W6749927861"],"related_works":["https://openalex.org/W2385244905","https://openalex.org/W1554980273","https://openalex.org/W2021008485","https://openalex.org/W2352164403","https://openalex.org/W2317681159","https://openalex.org/W2771814581","https://openalex.org/W2368324430","https://openalex.org/W2616924144","https://openalex.org/W2355113740","https://openalex.org/W2030411253"],"abstract_inverted_index":{"We":[0,134],"tackle":[1],"the":[2,8,21,36,57,61,107,119,124,139],"problem":[3],"of":[4],"texture":[5,79],"inpainting":[6,34],"where":[7],"input":[9,99],"images":[10,149],"are":[11],"textures":[12],"with":[13,17,35,53,118,161],"missing":[14],"values":[15],"along":[16],"masks":[18],"that":[19,23,89,153],"indicate":[20],"zones":[22],"should":[24],"be":[25,64,68],"generated.":[26],"Many":[27],"works":[28,46],"have":[29],"been":[30],"done":[31],"in":[32,60,70,116],"image":[33,62],"aim":[37],"to":[38,63,67,72,105],"achieve":[39,73],"global":[40],"and":[41,76,95,128,151,158],"local":[42,58,74,162],"consistency.":[43],"But":[44],"these":[45],"still":[47],"suffer":[48],"from":[49],"limitations":[50],"when":[51],"dealing":[52],"textures.":[54],"In":[55],"fact,":[56],"information":[59],"completed":[65],"needs":[66],"used":[69],"order":[71],"continuities":[75],"visually":[77],"realistic":[78],"inpainting.":[80],"For":[81],"this,":[82],"we":[83,111],"propose":[84],"a":[85,91],"new":[86],"segmentor":[87],"discriminator":[88],"performs":[90],"patch-wise":[92],"real/fake":[93],"classification":[94],"is":[96],"supervised":[97],"by":[98],"masks.":[100],"During":[101],"training,":[102],"it":[103,154],"aims":[104],"locate":[106],"generated":[108],"parts":[109,115],"(which":[110],"will":[112],"call":[113],"fake":[114,129],"consistency":[117,163],"GAN":[120],"framework),":[121],"thus":[122],"making":[123],"difference":[125],"between":[126],"real":[127],"patches":[130],"given":[131],"one":[132],"image.":[133],"tested":[135],"our":[136],"approach":[137],"on":[138],"publicly":[140],"available":[141],"DTD":[142],"dataset,":[143],"as":[144,146],"well":[145],"Electo-Magnetic":[147],"borehole":[148],"dataset":[150],"showed":[152],"achieves":[155],"state-of-the-art":[156],"performances":[157],"better":[159],"deals":[160],"than":[164],"existing":[165],"methods.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
