{"id":"https://openalex.org/W4414360678","doi":"https://doi.org/10.24963/ijcai.2025/99","title":"VidEvo: Evolving Video Editing through Exhaustive Temporal Modeling","display_name":"VidEvo: Evolving Video Editing through Exhaustive Temporal Modeling","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414360678","doi":"https://doi.org/10.24963/ijcai.2025/99"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/99","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/99","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5111088155","display_name":"Sizhe Dang","orcid":"https://orcid.org/0009-0007-5689-6490"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sizhe Dang","raw_affiliation_strings":["Xi'an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026287754","display_name":"Huan Liu","orcid":"https://orcid.org/0000-0002-7780-386X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Liu","raw_affiliation_strings":["Xi'an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100429675","display_name":"Mengmeng Wang","orcid":"https://orcid.org/0000-0002-9890-8900"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]},{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mengmeng Wang","raw_affiliation_strings":["SGIT AI Lab, State Grid Corporation of China","Zhejiang University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SGIT AI Lab, State Grid Corporation of China","institution_ids":["https://openalex.org/I17442442"]},{"raw_affiliation_string":"Zhejiang University of Technology","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066454748","display_name":"Xin Lai","orcid":"https://orcid.org/0000-0002-2565-1833"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Lai","raw_affiliation_strings":["Xi'an Jiaotong University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Xi'an Jiaotong University","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102152323","display_name":"Guang Dai","orcid":"https://orcid.org/0000-0002-3529-9087"},"institutions":[{"id":"https://openalex.org/I17442442","display_name":"State Grid Corporation of China (China)","ror":"https://ror.org/05twwhs70","country_code":"CN","type":"company","lineage":["https://openalex.org/I17442442"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guang Dai","raw_affiliation_strings":["SGIT AI Lab, State Grid Corporation of China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SGIT AI Lab, State Grid Corporation of China","institution_ids":["https://openalex.org/I17442442"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101879634","display_name":"Jingdong Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingdong Wang","raw_affiliation_strings":["Baidu Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Baidu Inc","institution_ids":["https://openalex.org/I98301712"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":"882","last_page":"890"},"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":0.9573000073432922,"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":0.9573000073432922,"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":0.9408000111579895,"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/embedding","display_name":"Embedding","score":0.5467000007629395},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.45239999890327454},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43529999256134033},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.388700008392334},{"id":"https://openalex.org/keywords/video-editing","display_name":"Video editing","score":0.3714999854564667},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.35109999775886536}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8338000178337097},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5467000007629395},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4749999940395355},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.45239999890327454},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.388700008392334},{"id":"https://openalex.org/C2780310081","wikidata":"https://www.wikidata.org/wiki/Q1154312","display_name":"Video editing","level":2,"score":0.3714999854564667},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.35109999775886536},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.337799996137619},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.3009999990463257},{"id":"https://openalex.org/C149810388","wikidata":"https://www.wikidata.org/wiki/Q5374873","display_name":"Emulation","level":2,"score":0.28940001130104065},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.28619998693466187},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.271699994802475},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27140000462532043}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/99","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/99","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"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":{"Text-guided":[0],"video":[1,45,91,102],"editing":[2,33,92,163],"(TGVE)":[3],"has":[4],"become":[5],"a":[6,44,88,137],"recent":[7],"hotspot":[8],"due":[9],"to":[10,48,56,77,103],"its":[11],"entertainment":[12],"value":[13],"and":[14,28,32,63,112,121,128,212,215],"practical":[15],"applications.":[16],"To":[17,132],"reduce":[18],"overhead,":[19],"existing":[20,71],"methods":[21],"primarily":[22],"extend":[23],"from":[24,99,126],"text-to-image":[25],"diffusion":[26],"models":[27],"typically":[29],"involve":[30],"reconstruction":[31,149],"phases.":[34],"However,":[35],"challenges":[36],"persist,":[37],"particularly":[38],"in":[39],"enhancing":[40],"temporal":[41,79,105,141,168,181,193,206],"consistency":[42,169],"of":[43,66,83,124,139,161,170],"while":[46],"adhering":[47],"textual":[49],"alignment":[50],"requirements.":[51],"A":[52],"crucial":[53],"factor":[54],"leading":[55],"the":[57,61,67,100,119,144,148,158,162,167,171,175],"aforementioned":[58],"issue":[59],"is":[60,74],"inadequate":[62],"implicit":[64],"tuning":[65],"attention":[68,114,159,186],"module":[69,160],"within":[70,143],"methods,":[72],"which":[73,191],"specifically":[75],"designed":[76],"capture":[78],"information.":[80],"In":[81],"light":[82],"this,":[84],"we":[85],"introduce":[86],"VidEvo,":[87],"novel":[89],"one-shot":[90],"method":[93],"that":[94,202],"leverages":[95],"explicit":[96],"cues":[97],"derived":[98],"original":[101],"enhance":[104],"modeling.":[106],"By":[107],"integrating":[108],"null-video":[109],"embedding":[110],"(NVE)":[111],"window-frame":[113],"(WFA)":[115],"components,":[116],"VidEvo":[117,203],"facilitates":[118],"smooth":[120],"coherent":[122],"generation":[123],"videos":[125],"global":[127],"local":[129,180],"perspectives":[130],"simultaneously.":[131],"be":[133],"specific,":[134],"NVE":[135,211],"learns":[136],"set":[138],"multi-scale":[140],"embeddings":[142,152],"visual":[145],"space":[146],"during":[147],"phase.":[150],"These":[151],"are":[153],"subsequently":[154],"directly":[155],"injected":[156],"into":[157],"phase,":[164],"explicitly":[165],"augmenting":[166],"entire":[172],"video.":[173],"On":[174],"other":[176,220],"hand,":[177],"WFA":[178],"enhances":[179,204],"modeling":[182],"by":[183],"dynamically":[184],"optimizing":[185],"mechanisms":[187],"between":[188],"adjacent":[189],"frames,":[190],"improves":[192],"coherence":[194],"with":[195,219],"reduced":[196],"computational":[197],"costs.":[198],"Experimental":[199],"evaluations":[200],"show":[201],"frame-to-frame":[205],"consistency.":[207],"Ablation":[208],"studies":[209],"confirm":[210],"WFA\u2019s":[213],"effectiveness":[214],"their":[216],"plug-and-play":[217],"capability":[218],"methods.":[221]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}