{"id":"https://openalex.org/W2966421984","doi":"https://doi.org/10.24963/ijcai.2019/276","title":"Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis","display_name":"Conditional GAN with Discriminative Filter Generation for Text-to-Video Synthesis","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2966421984","doi":"https://doi.org/10.24963/ijcai.2019/276","mag":"2966421984"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/276","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/276","pdf_url":"https://www.ijcai.org/proceedings/2019/0276.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0276.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5068290472","display_name":"Yogesh Balaji","orcid":null},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yogesh Balaji","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065576006","display_name":"Martin Renqiang Min","orcid":"https://orcid.org/0000-0002-8563-6133"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Martin Renqiang Min","raw_affiliation_strings":["NEC Labs America - Princeton"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Labs America - Princeton","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105038915","display_name":"Bing Bai","orcid":"https://orcid.org/0009-0009-9667-4969"},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Bing Bai","raw_affiliation_strings":["NEC Labs America - Princeton"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Labs America - Princeton","institution_ids":["https://openalex.org/I118347220"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102762707","display_name":"Rama Chellappa","orcid":"https://orcid.org/0000-0002-7638-1650"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rama Chellappa","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110182290","display_name":"Hans Peter Graf","orcid":null},"institutions":[{"id":"https://openalex.org/I118347220","display_name":"NEC (Japan)","ror":"https://ror.org/04jndar25","country_code":"JP","type":"company","lineage":["https://openalex.org/I118347220"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hans Peter Graf","raw_affiliation_strings":["NEC Labs America - Princeton"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NEC Labs America - Princeton","institution_ids":["https://openalex.org/I118347220"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":119,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1995","last_page":"2001"},"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":0.9986000061035156,"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":0.9986000061035156,"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":0.9763000011444092,"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":0.9695000052452087,"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/discriminative-model","display_name":"Discriminative model","score":0.8831483125686646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7699475884437561},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.730678915977478},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.6520891189575195},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5949507355690002},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.582337498664856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5667610168457031},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43056491017341614},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.14008787274360657},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07578814029693604}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8831483125686646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7699475884437561},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.730678915977478},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.6520891189575195},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5949507355690002},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.582337498664856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5667610168457031},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43056491017341614},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.14008787274360657},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07578814029693604},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/276","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/276","pdf_url":"https://www.ijcai.org/proceedings/2019/0276.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/276","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/276","pdf_url":"https://www.ijcai.org/proceedings/2019/0276.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966421984.pdf","grobid_xml":"https://content.openalex.org/works/W2966421984.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W1959608418","https://openalex.org/W2125389028","https://openalex.org/W2405756170","https://openalex.org/W2548275288","https://openalex.org/W2619947201","https://openalex.org/W2764019261","https://openalex.org/W2765512343","https://openalex.org/W2792263949","https://openalex.org/W2796136333","https://openalex.org/W2893749619","https://openalex.org/W2949099979","https://openalex.org/W2949999304","https://openalex.org/W2950776302","https://openalex.org/W2952716587","https://openalex.org/W2953030256","https://openalex.org/W2953133772","https://openalex.org/W2962793481","https://openalex.org/W2963092440","https://openalex.org/W2963169753","https://openalex.org/W2963373786","https://openalex.org/W2963567641","https://openalex.org/W2963966654","https://openalex.org/W2963981733","https://openalex.org/W2964031641","https://openalex.org/W2964033924","https://openalex.org/W2964242760","https://openalex.org/W4294643831","https://openalex.org/W4296979096","https://openalex.org/W4301206121","https://openalex.org/W4320013936","https://openalex.org/W4391602018"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W2366107444","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W4396941953","https://openalex.org/W2987280934"],"abstract_inverted_index":{"Developing":[0],"conditional":[1,36],"generative":[2],"models":[3],"for":[4],"text-to-video":[5],"synthesis":[6],"is":[7],"an":[8,12],"extremely":[9],"challenging":[10,68],"yet":[11],"important":[13],"topic":[14],"of":[15,79,103],"research":[16],"in":[17],"machine":[18],"learning.":[19],"In":[20,72],"this":[21,25],"work,":[22],"we":[23,74],"address":[24],"problem":[26],"by":[27],"introducing":[28],"Text-Filter":[29],"conditioning":[30,53,87],"Generative":[31],"Adversarial":[32],"Network":[33],"(TFGAN),":[34],"a":[35,40,56,76],"GAN":[37,58],"model":[38],"with":[39,55],"novel":[41,104],"multi-scale":[42],"text-conditioning":[43],"scheme":[44,54],"that":[45,92],"improves":[46],"text-video":[47],"associations.":[48],"By":[49],"combining":[50],"the":[51],"proposed":[52],"deep":[57],"architecture,":[59],"TFGAN":[60,93],"generates":[61],"high":[62],"quality":[63],"videos":[64,102],"from":[65],"text":[66],"on":[67],"real-world":[69],"video":[70],"datasets.":[71],"addition,":[73],"construct":[75],"synthetic":[77],"dataset":[78],"text-conditioned":[80],"moving":[81],"shapes":[82],"to":[83],"systematically":[84],"evaluate":[85],"our":[86],"scheme.":[88],"Extensive":[89],"experiments":[90],"demonstrate":[91],"significantly":[94],"outperforms":[95],"existing":[96],"approaches,":[97],"and":[98],"can":[99],"also":[100],"generate":[101],"categories":[105],"not":[106],"seen":[107],"during":[108],"training.":[109]},"counts_by_year":[{"year":2026,"cited_by_count":5},{"year":2025,"cited_by_count":24},{"year":2024,"cited_by_count":31},{"year":2023,"cited_by_count":20},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":12}],"updated_date":"2026-07-26T07:53:14.480251","created_date":"2025-10-10T00:00:00"}
