{"id":"https://openalex.org/W4402703066","doi":"https://doi.org/10.1109/cvpr52733.2024.00743","title":"Fast ODE-based Sampling for Diffusion Models in Around 5 Steps","display_name":"Fast ODE-based Sampling for Diffusion Models in Around 5 Steps","publication_year":2024,"publication_date":"2024-06-16","ids":{"openalex":"https://openalex.org/W4402703066","doi":"https://doi.org/10.1109/cvpr52733.2024.00743"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr52733.2024.00743","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52733.2024.00743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5039042766","display_name":"Zhenyu Zhou","orcid":"https://orcid.org/0000-0002-3344-4463"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenyu Zhou","raw_affiliation_strings":["Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101821806","display_name":"Defang Chen","orcid":"https://orcid.org/0000-0003-0833-7401"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Defang Chen","raw_affiliation_strings":["Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033018369","display_name":"Can Wang","orcid":"https://orcid.org/0000-0002-5890-4307"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Can Wang","raw_affiliation_strings":["Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003191821","display_name":"Chun Chen","orcid":"https://orcid.org/0000-0002-9279-8077"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chun Chen","raw_affiliation_strings":["Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,The State Key Laboratory of Blockchain and Data Security,China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":21.7828,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.99661132,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7777","last_page":"7786"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"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":0.98580002784729,"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/T11751","display_name":"Lattice Boltzmann Simulation Studies","score":0.9800999760627747,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/ode","display_name":"Ode","score":0.8164887428283691},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6426162719726562},{"id":"https://openalex.org/keywords/diffusion","display_name":"Diffusion","score":0.6116527318954468},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.6008744835853577},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.34035372734069824},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.31866031885147095},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2004338502883911},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09892413020133972},{"id":"https://openalex.org/keywords/thermodynamics","display_name":"Thermodynamics","score":0.09494787454605103},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.09149789810180664}],"concepts":[{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.8164887428283691},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6426162719726562},{"id":"https://openalex.org/C69357855","wikidata":"https://www.wikidata.org/wiki/Q163214","display_name":"Diffusion","level":2,"score":0.6116527318954468},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6008744835853577},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.34035372734069824},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.31866031885147095},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2004338502883911},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09892413020133972},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.09494787454605103},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.09149789810180664},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr52733.2024.00743","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr52733.2024.00743","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3792927286","display_name":null,"funder_award_id":"U1866602","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W967544008","https://openalex.org/W1503185336","https://openalex.org/W1505878979","https://openalex.org/W1861492603","https://openalex.org/W1901129140","https://openalex.org/W1959608418","https://openalex.org/W1991111872","https://openalex.org/W2117539524","https://openalex.org/W2170316986","https://openalex.org/W2913754224","https://openalex.org/W2959300817","https://openalex.org/W2962770929","https://openalex.org/W2990138404","https://openalex.org/W2997123088","https://openalex.org/W3004970274","https://openalex.org/W3032032567","https://openalex.org/W3036167779","https://openalex.org/W3118608800","https://openalex.org/W3119800657","https://openalex.org/W4211127940","https://openalex.org/W4221139906","https://openalex.org/W4250954493","https://openalex.org/W4256175784","https://openalex.org/W4281661987","https://openalex.org/W4297676498","https://openalex.org/W4301206121","https://openalex.org/W4308167501","https://openalex.org/W4312933868","https://openalex.org/W4318171169","https://openalex.org/W4320013936","https://openalex.org/W4320343052","https://openalex.org/W4321393095","https://openalex.org/W4323706282","https://openalex.org/W4379089575","https://openalex.org/W4380352311","https://openalex.org/W4386072096","https://openalex.org/W4387723644","https://openalex.org/W6640124913","https://openalex.org/W6640963894","https://openalex.org/W6677085345","https://openalex.org/W6679045638","https://openalex.org/W6765775151","https://openalex.org/W6765779288","https://openalex.org/W6779823529","https://openalex.org/W6783713337","https://openalex.org/W6786375611","https://openalex.org/W6788664344","https://openalex.org/W6788990321","https://openalex.org/W6790978476","https://openalex.org/W6795288823","https://openalex.org/W6797906067","https://openalex.org/W6809884996","https://openalex.org/W6810093873","https://openalex.org/W6810590380","https://openalex.org/W6810627792","https://openalex.org/W6811424244","https://openalex.org/W6838452192","https://openalex.org/W6838639034","https://openalex.org/W6838990407","https://openalex.org/W6843731886","https://openalex.org/W6846168004","https://openalex.org/W6849745102","https://openalex.org/W6850346274","https://openalex.org/W6850614898","https://openalex.org/W6850634621","https://openalex.org/W6853339897","https://openalex.org/W6857516785"],"related_works":["https://openalex.org/W2371448224","https://openalex.org/W3134495997","https://openalex.org/W2363680170","https://openalex.org/W2376428685","https://openalex.org/W4256082577","https://openalex.org/W625783435","https://openalex.org/W2048742619","https://openalex.org/W2384641672","https://openalex.org/W2742179975","https://openalex.org/W2362647823"],"abstract_inverted_index":{"Sampling":[0],"from":[1,141],"diffusion":[2,114],"models":[3],"can":[4,119],"be":[5,120],"treated":[6],"as":[7,24,31,123],"solving":[8],"the":[9,16,48,78,93,109,138,146],"corresponding":[10],"ordinary":[11],"differential":[12],"equations":[13],"(ODEs),":[14],"with":[15,23,67,137],"aim":[17],"of":[18,27,148],"obtaining":[19],"an":[20],"accurate":[21],"solution":[22],"few":[25],"number":[26],"function":[28],"evaluations":[29],"(NFE)":[30],"possible.":[32],"Recently,":[33],"various":[34],"fast":[35,113],"samplers":[36],"utilizing":[37],"higher-order":[38],"ODE":[39],"solvers":[40],"have":[41],"emerged":[42],"and":[43,166],"achieved":[44],"better":[45],"performance":[46],"than":[47],"initial":[49],"first-order":[50],"one.":[51],"However,":[52],"these":[53],"numerical":[54],"methods":[55],"inherently":[56],"result":[57],"in":[58,87,92],"certain":[59],"approximation":[60],"errors,":[61],"which":[62],"significantly":[63],"degrades":[64],"sample":[65],"quality":[66],"extremely":[68],"small":[69],"NFE":[70],"(e.g.,":[71],"around":[72],"5).":[73],"In":[74],"contrast,":[75],"based":[76],"on":[77,134,159,163,169],"geometric":[79],"observation":[80],"that":[81,102],"each":[82],"sampling":[83],"trajectory":[84],"almost":[85],"lies":[86],"a":[88,124],"two-dimensional":[89],"subspace":[90],"embedded":[91],"ambient":[94],"space,":[95],"we":[96,155],"propose":[97],"Approximate":[98],"MEan-Direction":[99],"Solver":[100],"(AMED-Solver)":[101],"eliminates":[103],"truncation":[104],"errors":[105],"by":[106],"directly":[107],"learning":[108],"mean":[110],"direction":[111],"for":[112],"sampling.":[115],"Besides,":[116],"our":[117,149],"method":[118],"easily":[121],"used":[122],"plugin":[125],"to":[126,143],"further":[127],"improve":[128],"existing":[129],"ODE-based":[130],"samplers.":[131],"Extensive":[132],"experiments":[133],"image":[135],"synthesis":[136],"resolution":[139],"ranging":[140],"32":[142],"512":[144],"demonstrate":[145],"effectiveness":[147],"method.":[150],"With":[151],"only":[152],"5":[153],"NFE,":[154],"achieve":[156],"6.61":[157],"FID":[158,162,168],"CIFAR-10,":[160],"10.74":[161],"ImageNet$64\\times":[164],"64$,":[165],"13.20":[167],"LSUN":[170],"Bedroom.":[171],"Our":[172],"code":[173],"is":[174],"available":[175],"at":[176],"https:/github.com/zju-pi/diff-sampler.":[177]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":7}],"updated_date":"2026-08-15T07:11:24.734988","created_date":"2025-10-10T00:00:00"}