{"id":"https://openalex.org/W2944955220","doi":"https://doi.org/10.1109/wacv45572.2020.9093322","title":"CrossNet: Latent Cross-Consistency for Unpaired Image Translation","display_name":"CrossNet: Latent Cross-Consistency for Unpaired Image Translation","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W2944955220","doi":"https://doi.org/10.1109/wacv45572.2020.9093322","mag":"2944955220"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093322","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093322","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1901.04530","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037433572","display_name":"Omry Sendik","orcid":"https://orcid.org/0000-0002-9268-8281"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Omry Sendik","raw_affiliation_strings":["Tel Aviv University","Tel Aviv University *"],"affiliations":[{"raw_affiliation_string":"Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"Tel Aviv University *","institution_ids":["https://openalex.org/I16391192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091260693","display_name":"Dani Lischinski","orcid":"https://orcid.org/0000-0002-6191-0361"},"institutions":[{"id":"https://openalex.org/I197251160","display_name":"Hebrew University of Jerusalem","ror":"https://ror.org/03qxff017","country_code":"IL","type":"education","lineage":["https://openalex.org/I197251160"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Dani Lischinski","raw_affiliation_strings":["The Hebrew University of Jerusalem","The Hebrew university of Jerusalem"],"affiliations":[{"raw_affiliation_string":"The Hebrew University of Jerusalem","institution_ids":["https://openalex.org/I197251160"]},{"raw_affiliation_string":"The Hebrew university of Jerusalem","institution_ids":["https://openalex.org/I197251160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036688260","display_name":"Daniel Cohen\u2010Or","orcid":"https://orcid.org/0000-0001-6777-7445"},"institutions":[{"id":"https://openalex.org/I16391192","display_name":"Tel Aviv University","ror":"https://ror.org/04mhzgx49","country_code":"IL","type":"education","lineage":["https://openalex.org/I16391192"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Daniel Cohen-Or","raw_affiliation_strings":["Tel Aviv University","Tel Aviv University *"],"affiliations":[{"raw_affiliation_string":"Tel Aviv University","institution_ids":["https://openalex.org/I16391192"]},{"raw_affiliation_string":"Tel Aviv University *","institution_ids":["https://openalex.org/I16391192"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5037433572"],"corresponding_institution_ids":["https://openalex.org/I16391192"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00394547,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3032","last_page":"3040"},"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":0.9984999895095825,"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":0.9984999895095825,"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":0.9879999756813049,"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/T10515","display_name":"Cancer-related molecular mechanisms research","score":0.9747999906539917,"subfield":{"id":"https://openalex.org/subfields/1306","display_name":"Cancer Research"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.7734016180038452},{"id":"https://openalex.org/keywords/image-translation","display_name":"Image translation","score":0.765850305557251},{"id":"https://openalex.org/keywords/translation","display_name":"Translation (biology)","score":0.7616195678710938},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.699856698513031},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.6867878437042236},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.6033436059951782},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.49823808670043945},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4638514518737793},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3820495903491974},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3568381369113922},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3337205648422241},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05609714984893799}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.7734016180038452},{"id":"https://openalex.org/C2779757391","wikidata":"https://www.wikidata.org/wiki/Q6002292","display_name":"Image translation","level":3,"score":0.765850305557251},{"id":"https://openalex.org/C149364088","wikidata":"https://www.wikidata.org/wiki/Q185917","display_name":"Translation (biology)","level":4,"score":0.7616195678710938},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.699856698513031},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.6867878437042236},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.6033436059951782},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.49823808670043945},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4638514518737793},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3820495903491974},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3568381369113922},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3337205648422241},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05609714984893799},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C105580179","wikidata":"https://www.wikidata.org/wiki/Q188928","display_name":"Messenger RNA","level":3,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093322","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093322","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1901.04530","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.04530","pdf_url":"https://arxiv.org/pdf/1901.04530","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"mag:2944955220","is_oa":true,"landing_page_url":"https://arxiv.org/abs/1901.04530v2","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1901.04530","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1901.04530","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1901.04530","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1901.04530","pdf_url":"https://arxiv.org/pdf/1901.04530","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2944955220.pdf","grobid_xml":"https://content.openalex.org/works/W2944955220.grobid-xml"},"referenced_works_count":38,"referenced_works":["https://openalex.org/W1909211582","https://openalex.org/W2093848332","https://openalex.org/W2099471712","https://openalex.org/W2124351162","https://openalex.org/W2331128040","https://openalex.org/W2339754110","https://openalex.org/W2579352881","https://openalex.org/W2593414223","https://openalex.org/W2607202125","https://openalex.org/W2797650215","https://openalex.org/W2807033398","https://openalex.org/W2807330048","https://openalex.org/W2882982468","https://openalex.org/W2885192629","https://openalex.org/W2943322963","https://openalex.org/W2951939904","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963142510","https://openalex.org/W2963245486","https://openalex.org/W2963444790","https://openalex.org/W2963709863","https://openalex.org/W2963723198","https://openalex.org/W2963767194","https://openalex.org/W2963784072","https://openalex.org/W2963890275","https://openalex.org/W2963981733","https://openalex.org/W6702130928","https://openalex.org/W6720691552","https://openalex.org/W6730095352","https://openalex.org/W6732662172","https://openalex.org/W6734074887","https://openalex.org/W6735204497","https://openalex.org/W6738027021","https://openalex.org/W6745718552","https://openalex.org/W6752009473","https://openalex.org/W6765779288","https://openalex.org/W6795104053"],"related_works":["https://openalex.org/W3024170457","https://openalex.org/W2911140874","https://openalex.org/W3108836539","https://openalex.org/W2930844574","https://openalex.org/W3044908778","https://openalex.org/W2996456609","https://openalex.org/W2951647648","https://openalex.org/W2901503500","https://openalex.org/W2890730698","https://openalex.org/W3084170234","https://openalex.org/W2963901923","https://openalex.org/W3012561436","https://openalex.org/W2996884129","https://openalex.org/W3080141621","https://openalex.org/W3037532699","https://openalex.org/W2903518565","https://openalex.org/W3047550313","https://openalex.org/W3025974655","https://openalex.org/W2982009537","https://openalex.org/W2897699732"],"abstract_inverted_index":{"Recent":[0],"GAN-based":[1],"architectures":[2],"have":[3],"been":[4],"able":[5,142],"to":[6,59,113,126,143],"deliver":[7],"impressive":[8],"performance":[9],"on":[10,118,148],"the":[11,49,61,65,119,145],"general":[12],"task":[13],"of":[14,26,64,95,102,151],"image-to-image":[15],"translation.":[16],"In":[17,69],"particular,":[18],"it":[19],"was":[20,52],"shown":[21],"that":[22,133],"a":[23,74,93,100,149],"wide":[24],"variety":[25,150],"image":[27,35,79,121,152],"translation":[28,67,122,153],"operators":[29],"may":[30],"be":[31],"learned":[32],"from":[33,39],"two":[34,40],"sets,":[36],"containing":[37],"images":[38],"different":[41],"domains,":[42],"without":[43],"establishing":[44],"an":[45],"explicit":[46],"pairing":[47],"between":[48,104],"images.":[50],"This":[51],"made":[53],"possible":[54],"by":[55,87],"introducing":[56],"clever":[57],"regularizers":[58,85],"overcome":[60],"under-constrained":[62],"nature":[63],"unpaired":[66,78],"problem.":[68],"this":[70],"work,":[71],"we":[72],"introduce":[73],"novel":[75],"architecture":[76,91,136],"for":[77],"translation,":[80],"and":[81,137],"explore":[82],"several":[83,115],"new":[84],"enabled":[86],"it.":[88],"Specifically,":[89],"our":[90,134],"comprises":[92],"pair":[94,101],"GANs,":[96],"as":[97,99,127],"well":[98],"translators":[103],"their":[105],"respective":[106],"latent":[107,128,138],"spaces.":[108],"These":[109],"cross-translators":[110],"enable":[111],"us":[112],"impose":[114],"regularizing":[116],"constraints":[117,140],"learnt":[120],"operator,":[123],"collectively":[124],"referred":[125],"cross-consistency.":[129],"Our":[130],"results":[131],"show":[132],"proposed":[135],"cross-consistency":[139],"are":[141],"outperform":[144],"existing":[146],"state-of-the-art":[147],"tasks.":[154]},"counts_by_year":[],"updated_date":"2026-02-09T09:26:11.010843","created_date":"2025-10-10T00:00:00"}
