{"id":"https://openalex.org/W4417280700","doi":"https://doi.org/10.1109/iccv51701.2025.01473","title":"The Curse of Conditions: Analyzing and Improving Optimal Transport for Conditional Flow-Based Generation","display_name":"The Curse of Conditions: Analyzing and Improving Optimal Transport for Conditional Flow-Based Generation","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4417280700","doi":"https://doi.org/10.1109/iccv51701.2025.01473"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2503.10636","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007305729","display_name":"Ho Kei Cheng","orcid":"https://orcid.org/0000-0002-8573-4809"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ho Kei Cheng","raw_affiliation_strings":["University of Illinois Urbana-Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049638480","display_name":"Alexander G. Schwing","orcid":null},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alexander Schwing","raw_affiliation_strings":["University of Illinois Urbana-Champaign"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois Urbana-Champaign","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5007305729"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37927777,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15875","last_page":"15884"},"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":0.4950000047683716,"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":0.4950000047683716,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.20389999449253082,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.051600001752376556,"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/weighting","display_name":"Weighting","score":0.5081999897956848},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.49050000309944153},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.4154999852180481},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.3928000032901764},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.392300009727478},{"id":"https://openalex.org/keywords/multiplicative-function","display_name":"Multiplicative function","score":0.3871999979019165},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.38499999046325684},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.3828999996185303},{"id":"https://openalex.org/keywords/cvar","display_name":"CVAR","score":0.3716000020503998},{"id":"https://openalex.org/keywords/conditional-probability-distribution","display_name":"Conditional probability distribution","score":0.367900013923645}],"concepts":[{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5105000138282776},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.5081999897956848},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.49050000309944153},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4401000142097473},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.4154999852180481},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4077000021934509},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.3928000032901764},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.392300009727478},{"id":"https://openalex.org/C42747912","wikidata":"https://www.wikidata.org/wiki/Q1048447","display_name":"Multiplicative function","level":2,"score":0.3871999979019165},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.38499999046325684},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.3828999996185303},{"id":"https://openalex.org/C2779922397","wikidata":"https://www.wikidata.org/wiki/Q5014755","display_name":"CVAR","level":4,"score":0.3716000020503998},{"id":"https://openalex.org/C43555835","wikidata":"https://www.wikidata.org/wiki/Q2300258","display_name":"Conditional probability distribution","level":2,"score":0.367900013923645},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.3612000048160553},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.35440000891685486},{"id":"https://openalex.org/C70136482","wikidata":"https://www.wikidata.org/wiki/Q13583781","display_name":"A-weighting","level":3,"score":0.35010001063346863},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.33640000224113464},{"id":"https://openalex.org/C131584629","wikidata":"https://www.wikidata.org/wiki/Q4308705","display_name":"Coupling (piping)","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.3328999876976013},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.33149999380111694},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.3310000002384186},{"id":"https://openalex.org/C2988881298","wikidata":"https://www.wikidata.org/wiki/Q16884885","display_name":"Transport theory","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3059999942779541},{"id":"https://openalex.org/C140479938","wikidata":"https://www.wikidata.org/wiki/Q5254619","display_name":"Iterated function","level":2,"score":0.30309998989105225},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C2778770139","wikidata":"https://www.wikidata.org/wiki/Q1966904","display_name":"Solver","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C34862557","wikidata":"https://www.wikidata.org/wiki/Q178985","display_name":"Ode","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.28450000286102295},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.28290000557899475},{"id":"https://openalex.org/C51544822","wikidata":"https://www.wikidata.org/wiki/Q465274","display_name":"Ordinary differential equation","level":3,"score":0.2791000008583069},{"id":"https://openalex.org/C51955184","wikidata":"https://www.wikidata.org/wiki/Q1545585","display_name":"Stochastic differential equation","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C149441793","wikidata":"https://www.wikidata.org/wiki/Q200726","display_name":"Probability distribution","level":2,"score":0.2743000090122223},{"id":"https://openalex.org/C186215838","wikidata":"https://www.wikidata.org/wiki/Q772232","display_name":"Conditional expectation","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C79772020","wikidata":"https://www.wikidata.org/wiki/Q5159264","display_name":"Conditional independence","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C149629883","wikidata":"https://www.wikidata.org/wiki/Q660926","display_name":"Fraction (chemistry)","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01473","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01473","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2503.10636","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.10636","pdf_url":"https://arxiv.org/pdf/2503.10636","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},{"id":"doi:10.48550/arxiv.2503.10636","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2503.10636","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2503.10636","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2503.10636","pdf_url":"https://arxiv.org/pdf/2503.10636","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"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"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1450433753","display_name":null,"funder_award_id":"2008387,2045586,2106825","funder_id":"https://openalex.org/F4320320373","funder_display_name":"National Stroke Foundation"},{"id":"https://openalex.org/G3147509767","display_name":null,"funder_award_id":"2020-67021-32799,OAC 2320345","funder_id":"https://openalex.org/F4320332299","funder_display_name":"National Institute of Food and Agriculture"}],"funders":[{"id":"https://openalex.org/F4320320373","display_name":"National Stroke Foundation","ror":"https://ror.org/004ckc033"},{"id":"https://openalex.org/F4320332299","display_name":"National Institute of Food and Agriculture","ror":"https://ror.org/05qx3fv49"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Minibatch":[0],"optimal":[1,45,54,108,124],"transport":[2,46,55,109,125],"coupling":[3],"straightens":[4],"paths":[5],"in":[6,40,60,117,140],"unconditional":[7],"flow":[8],"matching.":[9],"This":[10,49,90],"leads":[11,96],"to":[12,77,97,152],"computationally":[13],"less":[14,22],"demanding":[15],"inference":[16],"as":[17],"fewer":[18],"integration":[19],"steps":[20],"and":[21,81,94,137,144],"complex":[23],"numerical":[24],"solvers":[25],"can":[26],"be":[27],"employed":[28],"when":[29,121],"numerically":[30],"solving":[31],"an":[32],"ordinary":[33],"differential":[34],"equation":[35],"at":[36,70,164],"test":[37,71],"time.":[38],"However,":[39],"the":[41,52,78,85,118,123,153],"conditional":[42,107,114],"setting,":[43],"minibatch":[44],"falls":[47],"short.":[48],"is":[50,162],"because":[51],"default":[53],"mapping":[56],"disregards":[57],"conditions,":[58],"resulting":[59],"a":[61,98,113],"conditionally":[62],"skewed":[63,79],"prior":[64,88],"distribution":[65],"during":[66],"training.":[67],"In":[68],"contrast,":[69],"time,":[72],"we":[73,105],"have":[74],"no":[75],"access":[76],"prior,":[80],"instead":[82],"sample":[83],"from":[84],"full,":[86],"unbiased":[87],"distribution.":[89],"gap":[91],"between":[92],"training":[93],"testing":[95],"subpar":[99],"performance.":[100],"To":[101],"bridge":[102],"this":[103,130],"gap,":[104],"propose":[106],"C^2OT":[110],"that":[111,129],"adds":[112],"weighting":[115],"term":[116],"cost":[119],"matrix":[120],"computing":[122],"assignment.":[126],"Experiments":[127],"demonstrate":[128],"simple":[131],"fix":[132],"works":[133],"with":[134],"both":[135],"discrete":[136],"continuous":[138],"conditions":[139],"8gaussians-to-moons,":[141],"CIFAR-10,":[142],"ImageNet-32x32,":[143],"ImageNet-256x256.":[145],"Our":[146],"method":[147],"performs":[148],"better":[149],"overall":[150],"compared":[151],"existing":[154],"baselines":[155],"across":[156],"different":[157],"function":[158],"evaluation":[159],"budgets.":[160],"Code":[161],"available":[163],"https://hkchengrex.github.io/C2OT":[165]},"counts_by_year":[],"updated_date":"2026-05-06T06:03:25.996018","created_date":"2025-10-10T00:00:00"}