{"id":"https://openalex.org/W4379538630","doi":"https://doi.org/10.48550/arxiv.2306.01900","title":"Conditional Generation from Unconditional Diffusion Models using Denoiser Representations","display_name":"Conditional Generation from Unconditional Diffusion Models using Denoiser Representations","publication_year":2023,"publication_date":"2023-06-02","ids":{"openalex":"https://openalex.org/W4379538630","doi":"https://doi.org/10.48550/arxiv.2306.01900"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2306.01900","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.01900","pdf_url":"https://arxiv.org/pdf/2306.01900","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2306.01900","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5045360367","display_name":"Alexandros Graikos","orcid":"https://orcid.org/0009-0004-5170-1074","observed_orcids":["https://orcid.org/0009-0004-5170-1074"]},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Graikos, Alexandros","raw_affiliation_strings":["Stony Brook University NY , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University NY , USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065816086","display_name":"Srikar Yellapragada","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yellapragada, Srikar","raw_affiliation_strings":["Stony Brook University NY , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University NY , USA","institution_ids":["https://openalex.org/I59553526"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076307452","display_name":"Dimitris Samaras","orcid":"https://orcid.org/0000-0002-1373-0294","observed_orcids":["https://orcid.org/0000-0002-1373-0294"]},"institutions":[{"id":"https://openalex.org/I59553526","display_name":"Stony Brook University","ror":"https://ror.org/05qghxh33","country_code":"US","type":"education","lineage":["https://openalex.org/I59553526"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samaras, Dimitris","raw_affiliation_strings":["Stony Brook University NY , USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stony Brook University NY , USA","institution_ids":["https://openalex.org/I59553526"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59553526"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"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":1.0,"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":1.0,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.0,"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"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.0,"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/conditional-image-generation","display_name":"conditional image generation","score":0.8399999737739563},{"id":"https://openalex.org/keywords/denoising-diffusion-probabilistic-models","display_name":"denoising diffusion probabilistic models","score":0.8930000066757202},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"domain adaptation","score":0.5419999957084656},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.8489999771118164},{"id":"https://openalex.org/keywords/tiny-imagenet","display_name":"Tiny ImageNet","score":0.8690000176429749},{"id":"https://openalex.org/keywords/image-classification","display_name":"image classification","score":0.640999972820282}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7586413621902466},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5613829493522644},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5416861176490784},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.5372568964958191},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49363553524017334},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4757749140262604},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.43710583448410034},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.42706674337387085},{"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2306.01900","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.01900","pdf_url":"https://arxiv.org/pdf/2306.01900","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2306.01900","doi":"https://doi.org/10.48550/arxiv.2306.01900","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2306.01900","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2306.01900","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2306.01900","pdf_url":"https://arxiv.org/pdf/2306.01900","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,"listed_in":[],"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4379538630.pdf","grobid_xml":"https://content.openalex.org/works/W4379538630.grobid-xml"},"referenced_works_count":6,"referenced_works":["https://openalex.org/W2765407302","https://openalex.org/W2964121744","https://openalex.org/W2964137095","https://openalex.org/W4387211530","https://openalex.org/W4390873054","https://openalex.org/W4393148714"],"related_works":["https://openalex.org/W7162672492","https://openalex.org/W4280511821","https://openalex.org/W7223300414","https://openalex.org/W4407308820","https://openalex.org/W3170636531","https://openalex.org/W7160320330","https://openalex.org/W7162527055","https://openalex.org/W7167614108","https://openalex.org/W4390093110","https://openalex.org/W4387797285"],"abstract_inverted_index":{"Denoising":[0],"diffusion":[1,64,134],"models":[2,19,45,65,135],"have":[3],"gained":[4],"popularity":[5],"as":[6],"a":[7,127],"generative":[8],"modeling":[9],"technique":[10],"for":[11,144],"producing":[12],"high-quality":[13,141],"and":[14,93,129,139],"diverse":[15],"images.":[16],"Applying":[17],"these":[18,44],"to":[20,43,66,122,132,136],"downstream":[21],"tasks":[22],"requires":[23],"conditioning,":[24],"which":[25],"can":[26,46],"take":[27],"the":[28,70,75,80,101,114],"form":[29],"of":[30,37,74,82,117],"text,":[31],"class":[32],"labels,":[33],"or":[34,54],"other":[35],"forms":[36],"guidance.":[38],"However,":[39],"providing":[40],"conditioning":[41],"information":[42],"be":[47],"challenging,":[48],"particularly":[49],"when":[50],"annotations":[51],"are":[52],"scarce":[53],"imprecise.":[55],"In":[56],"this":[57],"paper,":[58],"we":[59,97],"propose":[60],"adapting":[61],"pre-trained":[62],"unconditional":[63],"new":[67,137],"conditions":[68,138],"using":[69],"learned":[71],"internal":[72],"representations":[73],"denoiser":[76],"network.":[77],"We":[78],"demonstrate":[79],"effectiveness":[81],"our":[83,111],"approach":[84,112,125],"on":[85],"various":[86,145],"conditional":[87,146],"generation":[88,92,147],"tasks,":[89],"including":[90],"attribute-conditioned":[91],"mask-conditioned":[94],"generation.":[95],"Additionally,":[96],"show":[98],"that":[99],"augmenting":[100],"Tiny":[102],"ImageNet":[103],"training":[104],"set":[105],"with":[106],"synthetic":[107],"images":[108],"generated":[109],"by":[110,120],"improves":[113],"classification":[115],"accuracy":[116],"ResNet":[118],"baselines":[119],"up":[121],"8%.":[123],"Our":[124],"provides":[126],"powerful":[128],"flexible":[130],"way":[131],"adapt":[133],"generate":[140],"augmented":[142],"data":[143],"tasks.":[148]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2023-06-07T00:00:00"}