{"id":"https://openalex.org/W4303648958","doi":"https://doi.org/10.1145/3610548.3618189","title":"Content-based Search for Deep Generative Models","display_name":"Content-based Search for Deep Generative Models","publication_year":2023,"publication_date":"2023-12-10","ids":{"openalex":"https://openalex.org/W4303648958","doi":"https://doi.org/10.1145/3610548.3618189"},"language":"en","primary_location":{"id":"doi:10.1145/3610548.3618189","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3610548.3618189","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3610548.3618189","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2023 Conference Papers","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3610548.3618189","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047680815","display_name":"Daohan Lu","orcid":"https://orcid.org/0000-0002-8733-6177"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Daohan Lu","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100715778","display_name":"Sheng-Yu Wang","orcid":"https://orcid.org/0000-0003-4000-2046"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sheng-Yu Wang","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000827309","display_name":"Nupur Kumari","orcid":"https://orcid.org/0000-0003-1799-1069"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nupur Kumari","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077668487","display_name":"Rohan Agarwal","orcid":"https://orcid.org/0009-0000-3525-5765"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rohan Agarwal","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107990963","display_name":"Mia Tang","orcid":"https://orcid.org/0009-0009-3553-3732"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mia Tang","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033305045","display_name":"David Bau","orcid":"https://orcid.org/0000-0003-1744-6765"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David Bau","raw_affiliation_strings":["Northeastern University, United States of America"],"affiliations":[{"raw_affiliation_string":"Northeastern University, United States of America","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102883508","display_name":"Jun-Yan Zhu","orcid":"https://orcid.org/0000-0001-8504-3410"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jun-Yan Zhu","raw_affiliation_strings":["Carnegie Mellon University, United States of America"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, United States of America","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5047680815"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":0.5924,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.66899368,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9983000159263611,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9983000159263611,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9973000288009644,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9972000122070312,"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/computer-science","display_name":"Computer science","score":0.8348619341850281},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.772953987121582},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7301559448242188},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6195645928382874},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.6074426174163818},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5758589506149292},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5619457364082336},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.5583791732788086},{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.4486598074436188},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4355139434337616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.419919490814209},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.11922281980514526}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8348619341850281},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.772953987121582},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7301559448242188},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6195645928382874},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.6074426174163818},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5758589506149292},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5619457364082336},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.5583791732788086},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.4486598074436188},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4355139434337616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.419919490814209},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.11922281980514526},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3610548.3618189","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3610548.3618189","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3610548.3618189","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2023 Conference Papers","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2210.03116","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2210.03116","pdf_url":"https://arxiv.org/pdf/2210.03116","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":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3610548.3618189","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3610548.3618189","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3610548.3618189","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2023 Conference Papers","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3699694763","display_name":"CAREER: Exploiting Deep Generative Models for Visual Recognition","funder_award_id":"2239076","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"},{"id":"https://openalex.org/F4320307786","display_name":"Adobe Systems","ror":"https://ror.org/059tvcg64"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4303648958.pdf","grobid_xml":"https://content.openalex.org/works/W4303648958.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W204268067","https://openalex.org/W1532325895","https://openalex.org/W1566135517","https://openalex.org/W1974647172","https://openalex.org/W1979931042","https://openalex.org/W2099736636","https://openalex.org/W2108598243","https://openalex.org/W2111993661","https://openalex.org/W2130660124","https://openalex.org/W2132201434","https://openalex.org/W2149557440","https://openalex.org/W2151103935","https://openalex.org/W2153404544","https://openalex.org/W2154956324","https://openalex.org/W2466618734","https://openalex.org/W2499468060","https://openalex.org/W2883672875","https://openalex.org/W2903893359","https://openalex.org/W2962770929","https://openalex.org/W2984648456","https://openalex.org/W3021157314","https://openalex.org/W3034600949","https://openalex.org/W3034855543","https://openalex.org/W3035574324","https://openalex.org/W3048800544","https://openalex.org/W3106976604","https://openalex.org/W3174480022","https://openalex.org/W3180059462","https://openalex.org/W3180355996","https://openalex.org/W3183544223","https://openalex.org/W3216352822","https://openalex.org/W4200095354","https://openalex.org/W4200150166","https://openalex.org/W4200559159","https://openalex.org/W4214582496","https://openalex.org/W4281485151","https://openalex.org/W4285981707","https://openalex.org/W4286611278","https://openalex.org/W4286980377","https://openalex.org/W4306809168","https://openalex.org/W4311001643","https://openalex.org/W4312353784","https://openalex.org/W4312443583","https://openalex.org/W4312529868","https://openalex.org/W4312694728","https://openalex.org/W4312933868","https://openalex.org/W4385271055","https://openalex.org/W4386072096","https://openalex.org/W4386076215","https://openalex.org/W4386113271","https://openalex.org/W4390873054","https://openalex.org/W6631834165","https://openalex.org/W6637101025","https://openalex.org/W6801986474"],"related_works":["https://openalex.org/W4365211920","https://openalex.org/W3014948380","https://openalex.org/W4380551139","https://openalex.org/W4317695495","https://openalex.org/W4395044357","https://openalex.org/W4287117424","https://openalex.org/W4387506531","https://openalex.org/W2087346071","https://openalex.org/W2967848559","https://openalex.org/W4299831724"],"abstract_inverted_index":{"The":[0],"growing":[1],"proliferation":[2],"of":[3,20,33,44,62,81],"customized":[4],"and":[5,40,105],"pretrained":[6],"generative":[7,45,57],"models":[8,49],"has":[9],"made":[10],"it":[11],"infeasible":[12],"for":[13,114,122,143],"a":[14,38,41,60,90,110,138],"user":[15],"to":[16,73,92,119],"be":[17],"fully":[18],"cognizant":[19],"every":[21],"model":[22,35,58,76,115,145],"in":[23],"existence.":[24],"To":[25],"address":[26],"this":[27,94],"need,":[28],"we":[29,64,108,141],"introduce":[30,89],"the":[31,48,53,66,75,78,86,97,144],"task":[32,68],"content-based":[34],"search:":[36],"given":[37,96],"query":[39,98,124],"large":[42],"set":[43],"models,":[46],"finding":[47],"that":[50,128],"best":[51],"match":[52],"query.":[54,87],"As":[55],"each":[56],"produces":[59],"distribution":[61],"images,":[63],"formulate":[65],"search":[67],"as":[69,85],"an":[70],"optimization":[71],"problem":[72],"select":[74],"with":[77],"highest":[79],"probability":[80,95],"generating":[82],"similar":[83],"content":[84],"We":[88,126],"formulation":[91],"approximate":[93],"from":[99],"different":[100],"modalities,":[101],"e.g.,":[102],"image,":[103],"sketch,":[104],"text.":[106],"Furthermore,":[107],"propose":[109],"contrastive":[111],"learning":[112],"framework":[113],"retrieval,":[116],"which":[117],"learns":[118],"adapt":[120],"features":[121],"various":[123],"modalities.":[125],"demonstrate":[127],"our":[129],"method":[130],"outperforms":[131],"several":[132],"baselines":[133],"on":[134],"Generative":[135],"Model":[136],"Zoo,":[137],"new":[139],"benchmark":[140],"create":[142],"retrieval":[146],"task.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
