{"id":"https://openalex.org/W2174358748","doi":"https://doi.org/10.1109/icip.2017.8297089","title":"Learning to generate images with perceptual similarity metrics","display_name":"Learning to generate images with perceptual similarity metrics","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2174358748","doi":"https://doi.org/10.1109/icip.2017.8297089","mag":"2174358748"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8297089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8297089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1511.06409","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061896635","display_name":"Jake Snell","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Jake Snell","raw_affiliation_strings":["University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047499478","display_name":"Karl Ridgeway","orcid":null},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]},{"id":"https://openalex.org/I2802236040","display_name":"University of Colorado System","ror":"https://ror.org/00jc20583","country_code":"US","type":"education","lineage":["https://openalex.org/I2802236040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Karl Ridgeway","raw_affiliation_strings":["University of Colorado, Boulder","University of Colorado Boulder"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Colorado, Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]},{"raw_affiliation_string":"University of Colorado Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048686150","display_name":"Renjie Liao","orcid":"https://orcid.org/0009-0001-1660-9959"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Renjie Liao","raw_affiliation_strings":["University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010202930","display_name":"Brett D. Roads","orcid":"https://orcid.org/0000-0002-9667-3909"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]},{"id":"https://openalex.org/I2802236040","display_name":"University of Colorado System","ror":"https://ror.org/00jc20583","country_code":"US","type":"education","lineage":["https://openalex.org/I2802236040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Brett D. Roads","raw_affiliation_strings":["University of Colorado, Boulder","University of Colorado Boulder"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Colorado, Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]},{"raw_affiliation_string":"University of Colorado Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047726287","display_name":"Michael C. Mozer","orcid":"https://orcid.org/0000-0002-9654-0575"},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]},{"id":"https://openalex.org/I2802236040","display_name":"University of Colorado System","ror":"https://ror.org/00jc20583","country_code":"US","type":"education","lineage":["https://openalex.org/I2802236040"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael C. Mozer","raw_affiliation_strings":["University of Colorado, Boulder","University of Colorado Boulder"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Colorado, Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]},{"raw_affiliation_string":"University of Colorado Boulder","institution_ids":["https://openalex.org/I188538660","https://openalex.org/I2802236040"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000111344","display_name":"Richard S. Zemel","orcid":"https://orcid.org/0000-0001-9353-7509"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Richard S. Zemel","raw_affiliation_strings":["University of Toronto"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Toronto","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1489,"has_fulltext":true,"cited_by_count":51,"citation_normalized_percentile":{"value":0.93733333,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4277","last_page":"4281"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9991000294685364,"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/T12859","display_name":"Cell Image Analysis Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1304","display_name":"Biophysics"},"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"}},{"id":"https://openalex.org/T13114","display_name":"Image Processing Techniques and Applications","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7528727054595947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6539463996887207},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.6125516295433044},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6007035970687866},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5696438550949097},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5472979545593262},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.49851202964782715},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4915412366390228},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4866798520088196},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4865967035293579},{"id":"https://openalex.org/keywords/structural-similarity","display_name":"Structural similarity","score":0.44503509998321533},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42006444931030273},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4168926179409027}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7528727054595947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539463996887207},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.6125516295433044},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6007035970687866},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5696438550949097},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5472979545593262},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.49851202964782715},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4915412366390228},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4866798520088196},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4865967035293579},{"id":"https://openalex.org/C139489369","wikidata":"https://www.wikidata.org/wiki/Q770846","display_name":"Structural similarity","level":2,"score":0.44503509998321533},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42006444931030273},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4168926179409027},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/icip.2017.8297089","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8297089","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1511.06409","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1511.06409","pdf_url":"https://arxiv.org/pdf/1511.06409","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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:2174358748","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1511.06409.pdf","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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.1511.06409","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1511.06409","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1511.06409","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1511.06409","pdf_url":"https://arxiv.org/pdf/1511.06409","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":[],"awards":[{"id":"https://openalex.org/G3273087600","display_name":null,"funder_award_id":"SES-1461535","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4462272880","display_name":null,"funder_award_id":"SBE\u20100542013","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G4496423624","display_name":"The Temporal Dynamics of Learning","funder_award_id":"0542013","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6513034700","display_name":"Temporal Dynamics of Learning","funder_award_id":"1041755","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6525329609","display_name":"Bayesian Optimization for Exploratory Experimentation in the Behavioral Sciences","funder_award_id":"1461535","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G810549051","display_name":null,"funder_award_id":"#SMA-1041755","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2174358748.pdf","grobid_xml":"https://content.openalex.org/works/W2174358748.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1487641199","https://openalex.org/W1547224907","https://openalex.org/W1580389772","https://openalex.org/W1597353101","https://openalex.org/W1710476689","https://openalex.org/W1791560514","https://openalex.org/W1813659000","https://openalex.org/W1850742715","https://openalex.org/W1885185971","https://openalex.org/W1959608418","https://openalex.org/W1984288074","https://openalex.org/W1986582056","https://openalex.org/W1990873664","https://openalex.org/W2009272644","https://openalex.org/W2026799324","https://openalex.org/W2043968544","https://openalex.org/W2046119925","https://openalex.org/W2047920195","https://openalex.org/W2092755522","https://openalex.org/W2107626382","https://openalex.org/W2108598243","https://openalex.org/W2118858186","https://openalex.org/W2121927366","https://openalex.org/W2125874614","https://openalex.org/W2126226185","https://openalex.org/W2133665775","https://openalex.org/W2136655611","https://openalex.org/W2136922672","https://openalex.org/W2145607950","https://openalex.org/W2162831671","https://openalex.org/W2166910890","https://openalex.org/W2173520492","https://openalex.org/W2181908415","https://openalex.org/W2243015210","https://openalex.org/W2265030536","https://openalex.org/W2286699414","https://openalex.org/W2396976214","https://openalex.org/W2430196102","https://openalex.org/W2520474966","https://openalex.org/W2626610348","https://openalex.org/W2949117887","https://openalex.org/W2951523806","https://openalex.org/W2963857374","https://openalex.org/W2964121744","https://openalex.org/W4377561911","https://openalex.org/W6629354409","https://openalex.org/W6632924624","https://openalex.org/W6634589695","https://openalex.org/W6636020080","https://openalex.org/W6638194035","https://openalex.org/W6638304892","https://openalex.org/W6676297131","https://openalex.org/W6677919164"],"related_works":["https://openalex.org/W2963713691","https://openalex.org/W2173520492","https://openalex.org/W2099471712","https://openalex.org/W2951523806","https://openalex.org/W2133665775","https://openalex.org/W3035335920","https://openalex.org/W2392185914","https://openalex.org/W2949117887","https://openalex.org/W2331128040","https://openalex.org/W2248556341","https://openalex.org/W1924619199","https://openalex.org/W1893585201","https://openalex.org/W1850742715","https://openalex.org/W1834627138","https://openalex.org/W1522301498","https://openalex.org/W3179080102","https://openalex.org/W1989726915","https://openalex.org/W3180814545","https://openalex.org/W3043012353","https://openalex.org/W2993837175"],"abstract_inverted_index":{"Deep":[0],"networks":[1,30,152],"are":[2,174],"increasingly":[3],"being":[4],"applied":[5],"to":[6,37,53,62,177],"problems":[7],"involving":[8],"image":[9,21,44,67,130,143],"synthesis,":[10],"e.g.,":[11],"generating":[12],"images":[13,103,166],"from":[14,22],"textual":[15],"descriptions":[16],"and":[17,45,132],"reconstructing":[18],"an":[19],"input":[20],"a":[23,33,42,55],"compact":[24],"representation.":[25],"Supervised":[26],"training":[27,97,127,171],"of":[28,66,90,126,150,170,179],"image-synthesis":[29],"typically":[31],"uses":[32],"pixel-wise":[34],"loss":[35,56,95],"(PL)":[36],"indicate":[38],"the":[39,69,88,124,148,168],"mismatch":[40],"between":[41],"generated":[43],"its":[46],"corresponding":[47],"target":[48],"image.":[49],"We":[50,86,121,156],"propose":[51],"instead":[52],"use":[54,169],"function":[57],"that":[58,158,173],"is":[59,77,80],"better":[60,140],"calibrated":[61],"human":[63,180],"perceptual":[64],"judgments":[65],"quality:":[68],"multiscale":[70],"structural-similarity":[71],"score":[72],"(MS-SSIM)":[73],"[1].":[74],"Because":[75],"MS-SSIM":[76,92],"differentiable,":[78],"it":[79],"easily":[81],"incorporated":[82],"into":[83],"gradient-descent":[84],"learning.":[85],"compare":[87],"consequences":[89],"using":[91],"versus":[93],"PL":[94,117],"on":[96,129,142],"autoencoders.":[98],"Human":[99],"observers":[100],"reliably":[101],"prefer":[102],"synthesized":[104,110],"by":[105,111],"MS-SSIM-optimized":[106],"models":[107],"over":[108],"those":[109],"PL-optimized":[112],"models,":[113],"for":[114,153],"two":[115],"distinct":[116],"measures":[118],"(L1and":[119],"L2distances).":[120],"also":[122],"explore":[123],"effect":[125],"objective":[128],"encoding":[131],"analyze":[133],"conditions":[134],"under":[135],"which":[136],"perceptually-optimized":[137,151],"representations":[138],"yield":[139],"performance":[141],"classification.":[144],"Finally,":[145],"we":[146],"demonstrate":[147],"superiority":[149],"super-resolution":[154],"imaging.":[155],"argue":[157],"significant":[159],"advances":[160],"can":[161],"be":[162],"made":[163],"in":[164],"modeling":[165],"through":[167],"objectives":[172],"well":[175],"aligned":[176],"characteristics":[178],"perception.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":7},{"year":2015,"cited_by_count":1}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}