{"id":"https://openalex.org/W4390446656","doi":"https://doi.org/10.1145/3617233.3617237","title":"Wasserstein loss for Semantic Editing in the Latent Space of GANs","display_name":"Wasserstein loss for Semantic Editing in the Latent Space of GANs","publication_year":2023,"publication_date":"2023-09-20","ids":{"openalex":"https://openalex.org/W4390446656","doi":"https://doi.org/10.1145/3617233.3617237"},"language":"en","primary_location":{"id":"doi:10.1145/3617233.3617237","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3617233.3617237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"20th International Conference on Content-based Multimedia Indexing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://hal.science/hal-04036414v1/document","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089610092","display_name":"Perla Doubinsky","orcid":"https://orcid.org/0009-0004-7181-2943"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Perla Doubinsky","raw_affiliation_strings":["Cnam, FR"],"affiliations":[{"raw_affiliation_string":"Cnam, FR","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070273069","display_name":"Nicolas Audebert","orcid":"https://orcid.org/0000-0001-6486-3102"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nicolas Audebert","raw_affiliation_strings":["Cnam, FR"],"affiliations":[{"raw_affiliation_string":"Cnam, FR","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028132236","display_name":"Michel Crucianu","orcid":"https://orcid.org/0000-0001-8204-6843"},"institutions":[{"id":"https://openalex.org/I124158823","display_name":"Conservatoire National des Arts et M\u00e9tiers","ror":"https://ror.org/0175hh227","country_code":"FR","type":"education","lineage":["https://openalex.org/I124158823","https://openalex.org/I4210134562"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Michel Crucianu","raw_affiliation_strings":["Cnam, France"],"affiliations":[{"raw_affiliation_string":"Cnam, France","institution_ids":["https://openalex.org/I124158823"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029449532","display_name":"Herv\u00e9 Le Borgne","orcid":"https://orcid.org/0000-0003-0520-8436"},"institutions":[{"id":"https://openalex.org/I4210085861","display_name":"Laboratoire d'Int\u00e9gration des Syst\u00e8mes et des Technologies","ror":"https://ror.org/000dbcc61","country_code":"FR","type":"government","lineage":["https://openalex.org/I2738703131","https://openalex.org/I2738703131","https://openalex.org/I277688954","https://openalex.org/I4210085861","https://openalex.org/I4210117989"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Herve Le Borgne","raw_affiliation_strings":["CEA LIST, FR"],"affiliations":[{"raw_affiliation_string":"CEA LIST, FR","institution_ids":["https://openalex.org/I4210085861"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5089610092"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4818,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.66780862,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"60"},"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":0.9998000264167786,"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":0.9998000264167786,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.993399977684021,"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/T10862","display_name":"AI in cancer detection","score":0.9866999983787537,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8305680751800537},{"id":"https://openalex.org/keywords/semantic-space","display_name":"Semantic space","score":0.6609624624252319},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6526466608047485},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.6045113205909729},{"id":"https://openalex.org/keywords/probabilistic-latent-semantic-analysis","display_name":"Probabilistic latent semantic analysis","score":0.5965582132339478},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5779967308044434},{"id":"https://openalex.org/keywords/latent-semantic-analysis","display_name":"Latent semantic analysis","score":0.5456730127334595},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.4554632604122162},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4477963149547577},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.4145847260951996},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3666185438632965},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.0675557553768158}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8305680751800537},{"id":"https://openalex.org/C2986420190","wikidata":"https://www.wikidata.org/wiki/Q39045939","display_name":"Semantic space","level":2,"score":0.6609624624252319},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6526466608047485},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.6045113205909729},{"id":"https://openalex.org/C112933361","wikidata":"https://www.wikidata.org/wiki/Q2845258","display_name":"Probabilistic latent semantic analysis","level":2,"score":0.5965582132339478},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5779967308044434},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.5456730127334595},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.4554632604122162},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4477963149547577},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.4145847260951996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3666185438632965},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0675557553768158},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3617233.3617237","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3617233.3617237","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"20th International Conference on Content-based Multimedia Indexing","raw_type":"proceedings-article"},{"id":"pmh:oai:HAL:hal-04036414v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04036414","pdf_url":"https://hal.science/hal-04036414v1/document","source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://cbmi2023.org/","raw_type":"Conference papers"}],"best_oa_location":{"id":"pmh:oai:HAL:hal-04036414v1","is_oa":true,"landing_page_url":"https://hal.science/hal-04036414","pdf_url":"https://hal.science/hal-04036414v1/document","source":{"id":"https://openalex.org/S4406922461","display_name":"SPIRE - Sciences Po Institutional REpository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://cbmi2023.org/","raw_type":"Conference papers"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390446656.pdf","grobid_xml":"https://content.openalex.org/works/W4390446656.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W385466589","https://openalex.org/W1834627138","https://openalex.org/W1932198206","https://openalex.org/W2962785568","https://openalex.org/W2969985801","https://openalex.org/W3035574324","https://openalex.org/W3176913662","https://openalex.org/W3177221875","https://openalex.org/W3204663154","https://openalex.org/W3209830847","https://openalex.org/W4286892689"],"related_works":["https://openalex.org/W2588002110","https://openalex.org/W2111020819","https://openalex.org/W2775171027","https://openalex.org/W2267563544","https://openalex.org/W2303774322","https://openalex.org/W1690254038","https://openalex.org/W2890241594","https://openalex.org/W4295564123","https://openalex.org/W4389358025","https://openalex.org/W2361268878"],"abstract_inverted_index":{"The":[0],"latent":[1,19],"space":[2,20],"of":[3,38,82],"GANs":[4],"contains":[5],"rich":[6],"semantics":[7],"reflecting":[8],"the":[9,36,64,80],"training":[10],"data.":[11],"Different":[12],"methods":[13,33],"propose":[14,58],"to":[15,22,27,40,48],"learn":[16],"edits":[17],"in":[18],"corresponding":[21],"semantic":[23],"attributes,":[24],"thus":[25],"allowing":[26],"modify":[28],"generated":[29],"images.":[30],"Most":[31],"supervised":[32],"rely":[34],"on":[35,63,85],"guidance":[37],"classifiers":[39,45],"produce":[41],"such":[42,69],"edits.":[43],"However,":[44],"can":[46],"lead":[47],"out-of-distribution":[49],"regions":[50],"and":[51,89],"be":[52],"fooled":[53],"by":[54],"adversarial":[55],"samples.":[56],"We":[57,78],"an":[59],"alternative":[60],"formulation":[61],"based":[62],"Wasserstein":[65],"loss":[66],"that":[67],"avoids":[68],"problems,":[70],"while":[71],"maintaining":[72],"performance":[73],"on-par":[74],"with":[75],"classifier-based":[76],"approaches.":[77],"demonstrate":[79],"effectiveness":[81],"our":[83],"method":[84],"two":[86],"datasets":[87],"(digits":[88],"faces)":[90],"using":[91],"StyleGAN2.":[92],"Code":[93],"is":[94],"available":[95],"at:":[96],"https://github.com/perladoubinsky/latent-wasserstein":[97]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-28T08:17:26.163206","created_date":"2025-10-10T00:00:00"}