{"id":"https://openalex.org/W7166113584","doi":"https://doi.org/10.48550/arxiv.2606.27345","title":"RayPE: Ray-Space Positional Encoding for 3D-Aware Video Generation","display_name":"RayPE: Ray-Space Positional Encoding for 3D-Aware Video Generation","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166113584","doi":"https://doi.org/10.48550/arxiv.2606.27345"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27345","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27345","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.2606.27345","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5139434847","display_name":"Minghao Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Minghao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015941605","display_name":"J Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Jiahao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5139408000","display_name":"Wenbo Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Wenbo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016584164","display_name":"Weidong Zhao","orcid":"https://orcid.org/0000-0003-4144-7303"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Wang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105217670","display_name":"Shan Ying","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ying, Shan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139444988","display_name":"Kai Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Kai","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":0.7120000123977661,"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":0.7120000123977661,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.04520000144839287,"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":0.04270000010728836,"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/bilinear-interpolation","display_name":"Bilinear interpolation","score":0.5218999981880188},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.48080000281333923},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.4794999957084656},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.47110000252723694},{"id":"https://openalex.org/keywords/reciprocal","display_name":"Reciprocal","score":0.4212000072002411},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.34040001034736633},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.32199999690055847},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.30869999527931213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6518999934196472},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5411999821662903},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5234000086784363},{"id":"https://openalex.org/C205203396","wikidata":"https://www.wikidata.org/wiki/Q612143","display_name":"Bilinear interpolation","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.48080000281333923},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4794999957084656},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C2777742833","wikidata":"https://www.wikidata.org/wiki/Q1964083","display_name":"Reciprocal","level":2,"score":0.4212000072002411},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.32199999690055847},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C82927061","wikidata":"https://www.wikidata.org/wiki/Q178192","display_name":"Cross product","level":2,"score":0.28929999470710754},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28439998626708984},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.28360000252723694},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C2781020372","wikidata":"https://www.wikidata.org/wiki/Q533093","display_name":"On the fly","level":2,"score":0.27320000529289246},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.2711000144481659},{"id":"https://openalex.org/C9376300","wikidata":"https://www.wikidata.org/wiki/Q168817","display_name":"Algebraic number","level":2,"score":0.27070000767707825},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.26809999346733093},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.26600000262260437},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26170000433921814},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.2529999911785126}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27345","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27345","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.2606.27345","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27345","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Modern":[0],"video":[1,145,195,214],"diffusion":[2],"transformers":[3],"position":[4],"their":[5],"tokens":[6],"through":[7],"RoPE":[8],"on":[9,68,216],"the":[10,17,25,29,34,44,52,56,61,85,98,105,112,141,164,171,180,202],"(u,v,t)":[11],"axes":[12],"--":[13,55,130],"a":[14,74,92,118,121,167,193,217],"description":[15],"of":[16,28,89,132,170],"camera's":[18],"sampling":[19],"grid":[20],"that":[21,33,77],"says":[22],"nothing":[23],"about":[24],"3D":[26,210],"structure":[27],"scene.":[30],"We":[31],"observe":[32],"geometric":[35],"relation":[36],"between":[37],"two":[38,53,125],"camera":[39,207],"rays":[40,54],"is":[41,49,110,197],"captured":[42],"by":[43,166],"Plucker":[45,81],"reciprocal":[46,106],"product,":[47],"which":[48,97,133],"bilinear":[50],"in":[51,64],"same":[57],"algebraic":[58],"form":[59],"as":[60],"dot":[62],"product":[63],"Transformer":[65],"attention.":[66],"Building":[67],"this":[69],"analogy,":[70],"we":[71,155],"propose":[72],"RayPE,":[73],"positional-encoding":[75],"extension":[76],"injects":[78],"per-token":[79],"6D":[80],"coordinates":[82],"additively":[83],"into":[84,117],"queries":[86],"and":[87,124,127,173,205,212],"keys":[88],"self-attention,":[90],"with":[91,104,147,179],"query/key":[93],"flip":[94],"arrangement":[95],"under":[96],"symmetric":[99],"identity":[100],"configuration":[101],"coincides":[102],"exactly":[103],"product.":[107],"The":[108,184],"injection":[109],"additive,":[111],"resulting":[113],"attention":[114],"score":[115],"decomposes":[116],"content":[119,126,182],"term,":[120,123],"geometry":[122,128],"cross-terms":[129],"all":[131],"our":[134],"experiments":[135],"find":[136],"individually":[137],"necessary.":[138],"To":[139],"make":[140],"encoding":[142,165],"stable":[143],"across":[144],"data":[146],"heterogeneous":[148],"camera-translation":[149],"scales":[150],"(SfM,":[151],"deep":[152],"SLAM,":[153],"metric),":[154],"further":[156],"decouple":[157],"ray":[158],"direction":[159],"from":[160,201],"moment":[161],"magnitude,":[162],"gate":[163],"learned":[168],"function":[169],"log-magnitude,":[172],"apply":[174],"RMSNorm":[175],"to":[176,192,199],"align":[177],"it":[178],"QKNorm-normalized":[181],"branch.":[183],"full":[185],"module":[186],"adds":[187],"less":[188],"than":[189],"0.1%":[190],"parameters":[191],"pretrained":[194,203],"DiT,":[196],"zero-initialized":[198],"start":[200],"weights,":[204],"improves":[206],"controllability,":[208],"cross-frame":[209],"consistency,":[211],"overall":[213],"quality":[215],"four-dataset":[218],"training":[219],"mixture.":[220]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-27T00:00:00"}
