{"id":"https://openalex.org/W7165952740","doi":"https://doi.org/10.48550/arxiv.2606.26058","title":"DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation","display_name":"DomainShuttle: Freeform Open Domain Subject-driven Text-to-video Generation","publication_year":2026,"publication_date":"2026-06-24","ids":{"openalex":"https://openalex.org/W7165952740","doi":"https://doi.org/10.48550/arxiv.2606.26058"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.26058","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26058","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.26058","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139345760","display_name":"Nan Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Nan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139308057","display_name":"Yiyang Cai","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cai, Yiyang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139311057","display_name":"Rongchang Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xie, Rongchang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057847376","display_name":"Junwen Pan","orcid":"https://orcid.org/0000-0002-8781-6090"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pan, Junwen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139344523","display_name":"Cheng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Cheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009148506","display_name":"Weinan Jia","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jia, Weinan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139365541","display_name":"Zhuowei Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Zhuowei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139372690","display_name":"Wen Zhou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Wen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139374588","display_name":"Zhenbang Sun","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sun, Zhenbang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139314174","display_name":"Wenhan Luo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Wenhan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":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":0.6050999760627747,"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":0.6050999760627747,"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":0.12309999763965607,"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/T12290","display_name":"Human Motion and Animation","score":0.03519999980926514,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.6438000202178955},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6011999845504761},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.5177000164985657},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4830000102519989},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4778999984264374},{"id":"https://openalex.org/keywords/subject","display_name":"Subject (documents)","score":0.4562000036239624},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.3675999939441681},{"id":"https://openalex.org/keywords/ideal","display_name":"Ideal (ethics)","score":0.3662000000476837}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7833999991416931},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.6438000202178955},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6011999845504761},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.5177000164985657},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.511900007724762},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4778999984264374},{"id":"https://openalex.org/C2777855551","wikidata":"https://www.wikidata.org/wiki/Q12310021","display_name":"Subject (documents)","level":2,"score":0.4562000036239624},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.3675999939441681},{"id":"https://openalex.org/C2776639384","wikidata":"https://www.wikidata.org/wiki/Q840396","display_name":"Ideal (ethics)","level":2,"score":0.3662000000476837},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3395000100135803},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.2881999909877777},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27649998664855957},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.27140000462532043},{"id":"https://openalex.org/C42357961","wikidata":"https://www.wikidata.org/wiki/Q213363","display_name":"Open set","level":2,"score":0.27059999108314514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2660999894142151},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.26489999890327454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2522999942302704}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.26058","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26058","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.26058","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.26058","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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.429368793964386,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Open":[0,14],"domain":[1,15,82,125,211],"subject-driven":[2],"text-to-video":[3],"(S2V)":[4],"generation":[5],"has":[6],"drawn":[7],"significant":[8,195],"interest":[9],"in":[10,63,72,103,164],"academia":[11],"and":[12,33,70,106,120,135,138,161,174,205],"industry.":[13],"S2V":[16,92],"mainly":[17],"involves":[18],"two":[19],"scenarios:":[20],"in-domain,":[21],"which":[22,35,66,115,132,156,178],"requires":[23],"retaining":[24],"the":[25,37,41,52,140,152],"reference":[26,136,147,158],"subject":[27,42,61,183,203],"features":[28,39,137,184],"as":[29,31,76],"much":[30],"possible,":[32],"cross-domain,":[34],"preserves":[36],"intrinsic":[38,182],"of":[40,146],"while":[43],"allowing":[44],"subject-irrelevant":[45],"properties":[46],"to":[47,51,168,180],"vary":[48],"flexibly":[49,95],"according":[50],"text":[53],"prompt.":[54],"Existing":[55],"methods":[56],"primarily":[57],"focus":[58],"on":[59],"maximizing":[60],"fidelity":[62,119,204],"in-domain":[64,105],"scenarios,":[65,74],"limits":[67],"their":[68],"editability":[69],"adaptability":[71],"cross-domain":[73,107],"such":[75],"novel":[77],"styles,":[78],"semantic":[79],"combinations,":[80],"or":[81],"attributes.":[83],"In":[84],"this":[85,110],"study,":[86],"we":[87,112,129],"propose":[88,113],"that":[89,192],"an":[90],"ideal":[91],"method":[93],"should":[94],"shuttle":[96],"between":[97],"different":[98],"domains,":[99],"achieving":[100],"strong":[101],"performance":[102,196],"both":[104],"scenarios.":[108,213],"To":[109],"end,":[111],"DomainShuttle,":[114],"could":[116],"achieve":[117],"high":[118,202],"generative":[121,206],"flexibility":[122,207],"for":[123,143],"open":[124,210],"video":[126,162],"personalization.":[127],"Specifically,":[128],"introduce":[130,151],"Domain-MoT,":[131],"decouples":[133],"videos":[134],"introduces":[139],"domain-aware":[141],"AdaLN":[142],"domain-specific":[144],"modeling":[145],"images.":[148],"We":[149],"then":[150],"Video-Reference":[153],"DualRoPE":[154],"scheme,":[155],"places":[157],"image":[159],"tokens":[160,163],"separate":[165],"RoPE":[166],"spaces":[167],"enable":[169],"precise":[170],"subject-level":[171],"spatial":[172],"modeling,":[173],"Cross-Pair":[175],"Consistent":[176],"Loss,":[177],"aims":[179],"extract":[181],"unaffected":[185],"by":[186],"irrelevant":[187],"features.":[188],"Extensive":[189],"experiments":[190],"demonstrate":[191],"DomainShuttle":[193],"achieves":[194],"improvements":[197],"over":[198],"existing":[199],"methods,":[200],"exhibiting":[201],"across":[208],"diverse":[209],"application":[212]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-26T00:00:00"}
