{"id":"https://openalex.org/W7154133354","doi":"https://doi.org/10.48550/arxiv.2604.09201","title":"CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation","display_name":"CT-1: Vision-Language-Camera Models Transfer Spatial Reasoning Knowledge to Camera-Controllable Video Generation","publication_year":2026,"publication_date":"2026-04-10","ids":{"openalex":"https://openalex.org/W7154133354","doi":"https://doi.org/10.48550/arxiv.2604.09201"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09201","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.09201","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133490673","display_name":"Haoyu Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Haoyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133497567","display_name":"Zihao Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Zihao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133524693","display_name":"Jiaxi Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gu, Jiaxi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133506099","display_name":"Haoran Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Haoran","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065043599","display_name":"Qingping Zheng","orcid":"https://orcid.org/0000-0003-1484-3220"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zheng, Qingping","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133498117","display_name":"Pin Tang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tang, Pin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133512537","display_name":"Yeyin Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin, Yeyin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126219518","display_name":"Yuang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Yuang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133540060","display_name":"Junqi Cheng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cheng, Junqi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126245996","display_name":"Zenghui Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Zenghui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133502256","display_name":"Peng Shu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shu, Peng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133525028","display_name":"Zuxuan Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Zuxuan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133499847","display_name":"Yu-Gang Jiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiang, Yu-Gang","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":0.48330000042915344,"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":0.48330000042915344,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.21940000355243683,"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/T11439","display_name":"Video Analysis and Summarization","score":0.030300000682473183,"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/regularization","display_name":"Regularization (linguistics)","score":0.43309998512268066},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.39079999923706055},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.3813000023365021},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.362199991941452},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.3517000079154968},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.34450000524520874}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7598000168800354},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6345999836921692},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.605400025844574},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.43309998512268066},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.3517000079154968},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.34450000524520874},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.3179999887943268},{"id":"https://openalex.org/C2778852477","wikidata":"https://www.wikidata.org/wiki/Q313614","display_name":"Video camera","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.29809999465942383},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.28380000591278076},{"id":"https://openalex.org/C3018868555","wikidata":"https://www.wikidata.org/wiki/Q2918907","display_name":"Single camera","level":2,"score":0.2784999907016754}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09201","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":"doi:10.48550/arxiv.2604.09201","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09201","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":"Preprint"},"sustainable_development_goals":[{"score":0.7144818305969238,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Camera-controllable":[0],"video":[1,64,103,154],"generation":[2,65],"aims":[3],"to":[4,58,63,90,106],"synthesize":[5],"videos":[6,161],"with":[7,114],"flexible":[8],"and":[9,75,130,153,158,162],"physically":[10],"plausible":[11],"camera":[12,20,30,69,94,110,164],"movements.":[13],"However,":[14],"existing":[15],"methods":[16],"either":[17],"provide":[18],"imprecise":[19],"control":[21,111,165],"from":[22],"text":[23],"prompts":[24],"or":[25],"rely":[26],"on":[27],"labor-intensive":[28],"manual":[29],"trajectory":[31,95],"parameters,":[32],"limiting":[33],"their":[34],"use":[35],"in":[36,86],"automated":[37],"scenarios.":[38],"To":[39,117],"address":[40],"these":[41],"issues,":[42],"we":[43,123],"propose":[44],"a":[45,54,76,82,102,125,133],"novel":[46],"Vision-Language-Camera":[47],"model,":[48,79],"termed":[49],"CT-1":[50,80],"(Camera":[51],"Transformer":[52,78],"1),":[53],"specialized":[55],"model":[56,105],"designed":[57],"transfer":[59],"spatial":[60,151],"reasoning":[61,152],"knowledge":[62],"by":[66,167],"accurately":[67],"estimating":[68],"trajectories.":[70],"Built":[71],"upon":[72],"vision-language":[73],"modules":[74],"Diffusion":[77],"employs":[81],"Wavelet-based":[83],"Regularization":[84],"Loss":[85],"the":[87,119,148],"frequency":[88],"domain":[89],"effectively":[91],"learn":[92],"complex":[93],"distributions.":[96],"These":[97],"trajectories":[98],"are":[99],"integrated":[100],"into":[101],"diffusion":[104],"enable":[107],"spatially":[108],"aware":[109],"that":[112,143],"aligns":[113],"user":[115],"intentions.":[116],"facilitate":[118],"training":[120],"of":[121],"CT-1,":[122],"design":[124],"dedicated":[126],"data":[127],"curation":[128],"pipeline":[129],"construct":[131],"CT-200K,":[132],"large-scale":[134],"dataset":[135],"containing":[136],"over":[137,169],"47M":[138],"frames.":[139],"Experimental":[140],"results":[141],"demonstrate":[142],"our":[144],"framework":[145],"successfully":[146],"bridges":[147],"gap":[149],"between":[150],"synthesis,":[155],"yielding":[156],"faithful":[157],"high-quality":[159],"camera-controllable":[160],"improving":[163],"accuracy":[166],"25.7%":[168],"prior":[170],"methods.":[171]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-14T00:00:00"}