{"id":"https://openalex.org/W4413277998","doi":"https://doi.org/10.1109/icip55913.2025.11084391","title":"RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-Plane Networks","display_name":"RAVEN: Rethinking Adversarial Video Generation with Efficient Tri-Plane Networks","publication_year":2025,"publication_date":"2025-08-18","ids":{"openalex":"https://openalex.org/W4413277998","doi":"https://doi.org/10.1109/icip55913.2025.11084391"},"language":"en","primary_location":{"id":"doi:10.1109/icip55913.2025.11084391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip55913.2025.11084391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Image Processing (ICIP)","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/A5077727233","display_name":"Partha Ghosh","orcid":"https://orcid.org/0000-0003-2843-2668"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Partha Ghosh","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems,T&#x00FC;bingen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems,T&#x00FC;bingen,Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068643077","display_name":"Soubhik Sanyal","orcid":null},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Soubhik Sanyal","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems,T&#x00FC;bingen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems,T&#x00FC;bingen,Germany","institution_ids":["https://openalex.org/I4210135521"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109890544","display_name":"Cordelia Schmid","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cordelia Schmid","raw_affiliation_strings":["PSL Research University,Inria, &#x00C9;cole Normale Sup&#x00E9;rieure, CNRS"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PSL Research University,Inria, &#x00C9;cole Normale Sup&#x00E9;rieure, CNRS","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044005697","display_name":"Bernhard Sch\u00f6lkopf","orcid":"https://orcid.org/0000-0002-8177-0925"},"institutions":[{"id":"https://openalex.org/I4210135521","display_name":"Max Planck Institute for Intelligent Systems","ror":"https://ror.org/04fq9j139","country_code":"DE","type":"facility","lineage":["https://openalex.org/I149899117","https://openalex.org/I4210135521"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bernhard Sch\u00f6lkopf","raw_affiliation_strings":["Max Planck Institute for Intelligent Systems,T&#x00FC;bingen,Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Max Planck Institute for Intelligent Systems,T&#x00FC;bingen,Germany","institution_ids":["https://openalex.org/I4210135521"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20756164,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1079","last_page":"1084"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9987999796867371,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.9987999796867371,"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":0.9980999827384949,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9965999722480774,"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/adversarial-system","display_name":"Adversarial system","score":0.8056973218917847},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7426162958145142},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5322081446647644},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43595170974731445}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8056973218917847},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7426162958145142},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5322081446647644},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43595170974731445}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip55913.2025.11084391","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip55913.2025.11084391","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2962770929","https://openalex.org/W2963092440","https://openalex.org/W2970641574","https://openalex.org/W3008102851","https://openalex.org/W3127039734","https://openalex.org/W3176179930","https://openalex.org/W3203570626","https://openalex.org/W3204588463","https://openalex.org/W4312423208","https://openalex.org/W4312453532","https://openalex.org/W4312473638","https://openalex.org/W4312722235","https://openalex.org/W4386071957","https://openalex.org/W4386075614","https://openalex.org/W4386075787","https://openalex.org/W4386076323","https://openalex.org/W4390872896","https://openalex.org/W4390874580","https://openalex.org/W4393153307","https://openalex.org/W4402876471"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"We":[0,101,189],"present":[1],"a":[2,25,129,134,143,157],"compute":[3],"and":[4,14,78,165,175,185,194],"data-efficient":[5],"video":[6,36,140,187],"generative":[7,33],"model":[8,137],"designed":[9],"to":[10,66,92,151],"address":[11],"long-term":[12],"spatial":[13],"temporal":[15],"dependencies.":[16],"To":[17],"capture":[18],"long":[19],"spatio-temporal":[20],"dependencies,":[21],"our":[22,73,85,114,136,168,192],"approach":[23,74,169],"incorporates":[24],"hybrid":[26],"explicit-implicit":[27],"tri-plane":[28,43],"representation":[29],"inspired":[30],"by":[31,107,128],"3D-aware":[32],"frameworks.":[34],"Individual":[35],"frames":[37],"are":[38,170],"synthesized":[39],"from":[40,48],"an":[41,109],"intermediate":[42],"representation,":[44],"which":[45],"is":[46],"derived":[47],"one":[49],"single":[50],"latent":[51],"code.":[52],"This":[53],"novel":[54],"strategy":[55],"more":[56,152],"than":[57,153],"halves":[58],"the":[59,67,76,96,104,125],"computational":[60],"complexity":[61],"measured":[62],"in":[63,90],"FLOPs":[64],"compared":[65],"most":[68],"efficient":[69,77],"state-of-the-art":[70],"methods.":[71],"Consequently,":[72],"facilitates":[75],"temporally":[79],"coherent":[80],"generation":[81,97],"of":[82,98,145,160,167],"videos.":[83],"Moreover,":[84],"joint":[86],"frame":[87,158],"modeling":[88],"approach,":[89],"contrast":[91],"autoregressive":[93],"methods,":[94],"mitigates":[95],"visual":[99],"artifacts.":[100],"further":[102],"enhance":[103],"model\u2019s":[105],"capabilities":[106],"integrating":[108],"optical":[110],"flow-based":[111],"module":[112],"within":[113],"Generative":[115],"Adversarial":[116],"Network":[117],"(GAN)":[118],"based":[119],"generator":[120,131],"architecture,":[121],"thereby":[122],"compensating":[123],"for":[124],"constraints":[126],"imposed":[127],"smaller":[130],"size.":[132],"As":[133],"result,":[135],"synthesizes":[138],"high-fidelity":[139],"clips":[141],"at":[142,156],"resolution":[144],"256\u00d7256":[146],"pixels,":[147],"with":[148],"durations":[149],"extending":[150],"5":[154],"seconds":[155],"rate":[159],"30":[161],"fps.":[162],"The":[163],"efficacy":[164],"versatility":[166],"empirically":[171],"validated":[172],"through":[173],"qualitative":[174],"quantitative":[176],"assessments":[177],"across":[178],"three":[179],"different":[180],"datasets":[181],"comprising":[182],"both":[183],"synthetic":[184],"real":[186],"clips.":[188],"will":[190],"make":[191],"training":[193],"inference":[195],"code":[196],"public.":[197]},"counts_by_year":[],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
