{"id":"https://openalex.org/W7224093441","doi":"https://doi.org/10.48550/arxiv.2610.36545","title":"FrameForge: Harnessing Priors of Video Foundation Models for Unified Image Generation","display_name":"FrameForge: Harnessing Priors of Video Foundation Models for Unified Image Generation","publication_year":2026,"publication_date":"2026-10-27","ids":{"openalex":"https://openalex.org/W7224093441","doi":"https://doi.org/10.48550/arxiv.2610.36545"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2610.36545","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.36545","pdf_url":"https://arxiv.org/pdf/2610.36545","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2610.36545","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5160023395","display_name":"Yijing Lin","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin, Yijing","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023341829","display_name":"Zhendong Mao","orcid":"https://orcid.org/0000-0001-5739-8126","observed_orcids":["https://orcid.org/0000-0001-5739-8126"]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mao, Zhendong","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160057449","display_name":"Mengqi Huang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huang, Mengqi","raw_affiliation_strings":["FrameX ","University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FrameX ","institution_ids":[]},{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5160005490","display_name":"Yuxin Wang","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yuxin","raw_affiliation_strings":["FrameX "],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"FrameX ","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5160030226","display_name":"Yongdong Zhang","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhang, Yongdong","raw_affiliation_strings":["University of Science and Technology of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":1.0,"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":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":9.999999747378752e-05,"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":0.0,"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/video-foundation-models","display_name":"video foundation models","score":0.9909999966621399},{"id":"https://openalex.org/keywords/temporal-relations","display_name":"temporal relations","score":0.515999972820282},{"id":"https://openalex.org/keywords/rope","display_name":"rope","score":0.5360000133514404},{"id":"https://openalex.org/keywords/attention-masks","display_name":"attention masks","score":0.47999998927116394},{"id":"https://openalex.org/keywords/image-editing","display_name":"image editing","score":0.9789999723434448}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7599999904632568},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6718000173568726},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.628000020980835},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.621399998664856},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5216000080108643},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5062999725341797},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.44110000133514404},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3422999978065491},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32899999618530273},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.2912999987602234},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C45493050","wikidata":"https://www.wikidata.org/wiki/Q7884934","display_name":"Unified Model","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C44492722","wikidata":"https://www.wikidata.org/wiki/Q327069","display_name":"Conditional probability","level":2,"score":0.27250000834465027},{"id":"https://openalex.org/C2776674983","wikidata":"https://www.wikidata.org/wiki/Q545981","display_name":"Image editing","level":3,"score":0.2563999891281128},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.2533000111579895}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2610.36545","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.36545","pdf_url":"https://arxiv.org/pdf/2610.36545","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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.2610.36545","doi":"https://doi.org/10.48550/arxiv.2610.36545","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2610.36545","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2610.36545","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2610.36545","pdf_url":"https://arxiv.org/pdf/2610.36545","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7224093441.pdf","grobid_xml":"https://content.openalex.org/works/W7224093441.grobid-xml"},"referenced_works_count":32,"referenced_works":["https://openalex.org/W3168867926","https://openalex.org/W4303647933","https://openalex.org/W4383472654","https://openalex.org/W4385848774","https://openalex.org/W4390722773","https://openalex.org/W4392538976","https://openalex.org/W4402387301","https://openalex.org/W4403321890","https://openalex.org/W4405032013","https://openalex.org/W4405035483","https://openalex.org/W4405096483","https://openalex.org/W4406789553","https://openalex.org/W4409092337","https://openalex.org/W4413147134","https://openalex.org/W4413157087","https://openalex.org/W4414929961","https://openalex.org/W4415337140","https://openalex.org/W4416071314","https://openalex.org/W4416601021","https://openalex.org/W4417098422","https://openalex.org/W4417170947","https://openalex.org/W4417271208","https://openalex.org/W6948058629","https://openalex.org/W6948505238","https://openalex.org/W7083319242","https://openalex.org/W7106651365","https://openalex.org/W7106828590","https://openalex.org/W7124336245","https://openalex.org/W7131079003","https://openalex.org/W7133190463","https://openalex.org/W7160094899","https://openalex.org/W7161717288"],"related_works":["https://openalex.org/W4416039564","https://openalex.org/W7212123635","https://openalex.org/W7106651365","https://openalex.org/W4393154148","https://openalex.org/W4393148423","https://openalex.org/W7083306376","https://openalex.org/W4387623658","https://openalex.org/W4413147473","https://openalex.org/W4415036042","https://openalex.org/W7124463778"],"abstract_inverted_index":{"Unified":[0],"conditional":[1,77],"image":[2,20,167],"generation":[3,59,78],"requires":[4],"a":[5,13,18,29,134,139],"single":[6],"model":[7,76],"to":[8,47,75],"preserve":[9],"different":[10,69,116],"aspects":[11,91],"of":[12,92,96,120],"visual":[14,34,66],"input":[15],"while":[16,61],"producing":[17],"target":[19,46,104,132],"that":[21,53,156],"follows":[22],"textual":[23],"guidance.":[24],"Pretrained":[25],"video":[26,62],"models":[27,63,100,124],"provide":[28],"promising":[30],"foundation":[31],"by":[32,109],"encoding":[33],"transformations":[35,67],"across":[36,58],"time,":[37],"yet":[38],"existing":[39],"approaches":[40],"typically":[41],"assign":[42],"the":[43,103,107,126,131,170],"condition":[44,108,127],"and":[45,153,166],"fixed":[48],"temporal":[49,70,82,112],"positions.":[50],"We":[51,84],"observe":[52],"condition-target":[54],"relationships":[55],"vary":[56],"substantially":[57],"tasks,":[60],"naturally":[64],"encode":[65],"at":[68],"scales.":[71],"This":[72],"motivates":[73],"us":[74],"through":[79,133,146],"input-adaptive":[80],"virtual":[81,117],"relations.":[83,94],"propose":[85],"FrameForge,":[86],"which":[87],"captures":[88],"two":[89],"complementary":[90],"such":[93],"Mixture":[95],"Temporal":[97,121],"Experts":[98],"(MoTE)":[99],"how":[101,125],"far":[102],"lies":[105],"from":[106],"dynamically":[110],"selecting":[111],"RoPE":[113],"experts":[114],"with":[115,138],"intervals.":[118],"Chain":[119],"Reasoning":[122],"(CoTR)":[123],"is":[128],"transformed":[129],"into":[130],"latent":[135],"intermediate":[136],"state,":[137],"reasoning-bottleneck":[140],"attention":[141],"mask":[142],"encouraging":[143],"information":[144],"propagation":[145],"this":[147],"pathway.":[148],"Experiments":[149],"on":[150],"DreamBench,":[151],"COCO2017,":[152],"GEdit-Bench":[154],"show":[155],"FrameForge":[157],"achieves":[158],"superior":[159],"performance":[160],"in":[161],"subject-driven":[162],"generation,":[163,165],"canny-to-image":[164],"editing":[168],"among":[169],"compared":[171],"methods.":[172]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-10-29T00:00:00"}