{"id":"https://openalex.org/W7154728252","doi":"https://doi.org/10.48550/arxiv.2604.15003","title":"Flow of Truth: Proactive Temporal Forensics for Image-to-Video Generation","display_name":"Flow of Truth: Proactive Temporal Forensics for Image-to-Video Generation","publication_year":2026,"publication_date":"2026-04-16","ids":{"openalex":"https://openalex.org/W7154728252","doi":"https://doi.org/10.48550/arxiv.2604.15003"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15003","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15003","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.15003","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133918067","display_name":"Yuzhuo Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Chen, Yuzhuo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133843904","display_name":"Zehua Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Zehua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133870500","display_name":"Han Fang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fang, Han","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133892807","display_name":"Hengyi Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Hengyi","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133905295","display_name":"Guanjie Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Guanjie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133908617","display_name":"Weiming Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Weiming","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5133918067"],"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.906499981880188,"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":0.906499981880188,"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":0.05559999868273735,"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/T12034","display_name":"Digital and Cyber Forensics","score":0.01759999990463257,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/pixel","display_name":"Pixel","score":0.7017999887466431},{"id":"https://openalex.org/keywords/tracing","display_name":"Tracing","score":0.6502000093460083},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.588100016117096},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.4884999990463257},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4683000147342682},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.41519999504089355},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4075999855995178}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.7017999887466431},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6983000040054321},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.6502000093460083},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.588100016117096},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5867999792098999},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5490999817848206},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.4884999990463257},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4683000147342682},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4075999855995178},{"id":"https://openalex.org/C556601545","wikidata":"https://www.wikidata.org/wiki/Q878553","display_name":"Computer forensics","level":3,"score":0.3919000029563904},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.3637000024318695},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.3160000145435333},{"id":"https://openalex.org/C2987933465","wikidata":"https://www.wikidata.org/wiki/Q141130","display_name":"Image manipulation","level":3,"score":0.29809999465942383},{"id":"https://openalex.org/C84418412","wikidata":"https://www.wikidata.org/wiki/Q3246940","display_name":"Digital forensics","level":2,"score":0.2872999906539917},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.25369998812675476},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.25110000371932983}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15003","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15003","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":"doi:10.48550/arxiv.2604.15003","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15003","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.6738972663879395,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"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],"rapid":[1],"rise":[2],"of":[3,71,124,132,167],"image-to-video":[4],"(I2V)":[5],"generation":[6,99,120],"enables":[7],"realistic":[8],"videos":[9],"to":[10,33],"be":[11],"created":[12],"from":[13,156],"a":[14,90,104,109,140,149],"single":[15],"image":[16,157],"but":[17],"also":[18],"brings":[19],"new":[20],"forensic":[21,91,142],"demands.":[22],"Unlike":[23],"static":[24],"images,":[25],"I2V":[26,82,174],"content":[27],"evolves":[28],"over":[29],"time,":[30],"requiring":[31],"forensics":[32,61,80,179],"move":[34],"beyond":[35],"2D":[36],"pixel-level":[37],"tampering":[38],"localization":[39],"toward":[40],"tracing":[41],"how":[42],"pixels":[43,125],"flow":[44,151],"and":[45,56,148,172],"transform":[46],"throughout":[47],"the":[48,73,98,130],"video.":[49],"As":[50],"frames":[51],"progress,":[52],"embedded":[53],"traces":[54],"drift":[55],"deform,":[57],"making":[58],"traditional":[59],"spatial":[60],"ineffective.":[62],"To":[63],"address":[64],"this":[65,113,136],"unexplored":[66],"dimension,":[67],"we":[68,116,138],"present":[69],"**Flow":[70],"Truth**,":[72],"first":[74],"proactive":[75],"framework":[76],"focusing":[77],"on":[78,135],"temporal":[79,161,178],"in":[81,88],"generation.":[83],"A":[84],"key":[85],"challenge":[86],"lies":[87],"discovering":[89],"signature":[92],"that":[93,144,153,165],"can":[94],"evolve":[95],"consistently":[96],"with":[97],"process,":[100],"which":[101],"is":[102],"inherently":[103],"creative":[105],"transformation":[106],"rather":[107,128],"than":[108,129],"deterministic":[110],"reconstruction.":[111],"Despite":[112],"intrinsic":[114],"difficulty,":[115],"innovatively":[117],"redefine":[118],"video":[119],"as":[121],"*the":[122],"motion":[123,147,155],"through":[126],"time":[127],"synthesis":[131],"frames*.":[133],"Building":[134],"view,":[137],"propose":[139],"learnable":[141],"template":[143],"follows":[145],"pixel":[146],"template-guided":[150],"module":[152],"decouples":[154],"content,":[158],"enabling":[159],"robust":[160],"tracing.":[162],"Experiments":[163],"show":[164],"Flow":[166],"Truth":[168],"generalizes":[169],"across":[170],"commercial":[171],"open-source":[173],"models,":[175],"substantially":[176],"improving":[177],"performance.":[180]},"counts_by_year":[],"updated_date":"2026-04-18T06:05:20.339008","created_date":"2026-04-18T00:00:00"}