{"id":"https://openalex.org/W4414739285","doi":"https://doi.org/10.1109/iccv51701.2025.01392","title":"Straighten Viscous Rectified Flow via Noise Optimization","display_name":"Straighten Viscous Rectified Flow via Noise Optimization","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4414739285","doi":"https://doi.org/10.1109/iccv51701.2025.01392"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.01392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01392","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":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2507.10218","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jimin Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jimin Dai","raw_affiliation_strings":["Nanjing University of Science and Technology,PCA Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,PCA Lab","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087163038","display_name":"Jiexi Yan","orcid":"https://orcid.org/0000-0002-2544-3057"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiexi Yan","raw_affiliation_strings":["Xidian University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xidian University","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101838351","display_name":"Jian Yang","orcid":"https://orcid.org/0009-0005-3925-845X"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Yang","raw_affiliation_strings":["Nanjing University of Science and Technology,PCA Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,PCA Lab","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101349412","display_name":"Lei Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Luo","raw_affiliation_strings":["Nanjing University of Science and Technology,PCA Lab"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology,PCA Lab","institution_ids":["https://openalex.org/I36399199"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"15005","last_page":"15014"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10360","display_name":"Fluid Dynamics and Turbulent Flows","score":0.9502999782562256,"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"}},"topics":[{"id":"https://openalex.org/T10360","display_name":"Fluid Dynamics and Turbulent Flows","score":0.9502999782562256,"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"}},{"id":"https://openalex.org/T11245","display_name":"Advanced Numerical Analysis Techniques","score":0.9071999788284302,"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"}},{"id":"https://openalex.org/T11379","display_name":"Rheology and Fluid Dynamics Studies","score":0.9010000228881836,"subfield":{"id":"https://openalex.org/subfields/1507","display_name":"Fluid Flow and Transfer Processes"},"field":{"id":"https://openalex.org/fields/15","display_name":"Chemical Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.7020999789237976},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5870000123977661},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4462999999523163},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.44269999861717224},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.40299999713897705},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.3734000027179718},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.366100013256073},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.3513000011444092}],"concepts":[{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.7020999789237976},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5870000123977661},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5354999899864197},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4462999999523163},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.44269999861717224},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40299999713897705},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3898000121116638},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.3734000027179718},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3732999861240387},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.3513000011444092},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.34630000591278076},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.31859999895095825},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.314300000667572},{"id":"https://openalex.org/C148043351","wikidata":"https://www.wikidata.org/wiki/Q4456944","display_name":"Current (fluid)","level":2,"score":0.3125999867916107},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2705000042915344},{"id":"https://openalex.org/C21080849","wikidata":"https://www.wikidata.org/wiki/Q13611879","display_name":"Data point","level":2,"score":0.2694000005722046},{"id":"https://openalex.org/C177454536","wikidata":"https://www.wikidata.org/wiki/Q578290","display_name":"Emphasis (telecommunications)","level":2,"score":0.26260000467300415},{"id":"https://openalex.org/C166693061","wikidata":"https://www.wikidata.org/wiki/Q5462119","display_name":"Flow velocity","level":3,"score":0.2587999999523163}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.01392","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.01392","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:2507.10218","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10218","pdf_url":"https://arxiv.org/pdf/2507.10218","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"},{"id":"doi:10.48550/arxiv.2507.10218","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2507.10218","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":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2507.10218","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2507.10218","pdf_url":"https://arxiv.org/pdf/2507.10218","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"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0],"Reflow":[1],"operation":[2],"aims":[3],"to":[4,45,51,114,131],"straighten":[5],"the":[6,10,25,112,118,121,126,167],"inference":[7],"trajectories":[8],"of":[9,27,120,169],"rectified":[11],"flow":[12],"during":[13],"training":[14,87],"by":[15,148],"constructing":[16],"deterministic":[17,60],"couplings":[18,61,134],"between":[19,55],"noises":[20],"and":[21,62,92,124,156,177],"images,":[22],"thereby":[23],"improving":[24],"quality":[26],"generated":[28],"images":[29,49,56,137],"in":[30,40,57,174],"single-step":[31],"or":[32],"few-step":[33,178],"generation.":[34],"However,":[35],"we":[36,69],"identify":[37],"critical":[38],"limitations":[39,168],"Reflow,":[41,170],"particularly":[42],"its":[43,58],"inability":[44],"rapidly":[46],"generate":[47],"high-quality":[48],"due":[50],"a":[52,71,85,93,103],"distribution":[53],"gap":[54],"constructed":[59],"real":[63,136,157],"images.":[64],"To":[65],"address":[66],"these":[67],"shortcomings,":[68],"propose":[70],"novel":[72],"alternative":[73],"called":[74],"Straighten":[75],"Viscous":[76],"Rectified":[77],"Flow":[78],"via":[79],"Noise":[80],"Optimization":[81],"(VRFNO),":[82],"which":[83,138],"is":[84],"joint":[86],"framework":[88],"integrating":[89],"an":[90],"encoder":[91],"neural":[94],"velocity":[95,105,119],"field.":[96],"VRFNO":[97,164],"introduces":[98],"two":[99],"key":[100],"innovations:":[101],"(1)":[102],"historical":[104],"term":[106],"that":[107,163],"enhances":[108],"trajectory":[109],"distinction,":[110],"enabling":[111],"model":[113],"more":[115],"accurately":[116],"predict":[117],"current":[122],"trajectory,":[123],"(2)":[125],"noise":[127],"optimization":[128],"through":[129],"reparameterization":[130],"form":[132],"optimized":[133],"with":[135,159],"are":[139],"then":[140],"utilized":[141],"for":[142],"training,":[143],"effectively":[144],"mitigating":[145],"errors":[146],"caused":[147],"Reflow's":[149],"limitations.":[150],"Comprehensive":[151],"experiments":[152],"on":[153],"synthetic":[154],"data":[155],"datasets":[158],"varying":[160],"resolutions":[161],"show":[162],"significantly":[165],"mitigates":[166],"achieving":[171],"state-of-the-art":[172],"performance":[173],"both":[175],"one-step":[176],"generation":[179],"tasks.":[180]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
