{"id":"https://openalex.org/W2891245376","doi":"https://doi.org/10.1109/icip.2018.8451079","title":"Long-Term Video Generation with Evolving Residual Video Frames","display_name":"Long-Term Video Generation with Evolving Residual Video Frames","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2891245376","doi":"https://doi.org/10.1109/icip.2018.8451079","mag":"2891245376"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451079","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451079","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/A5100348072","display_name":"Nayoung Kim","orcid":"https://orcid.org/0000-0003-3750-1290"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Nayoung Kim","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Ewha W. University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Ewha W. University, Seoul, Korea","institution_ids":["https://openalex.org/I138925566"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039192390","display_name":"Je\u2010Won Kang","orcid":"https://orcid.org/0000-0002-1637-9479"},"institutions":[{"id":"https://openalex.org/I138925566","display_name":"Ewha Womans University","ror":"https://ror.org/053fp5c05","country_code":"KR","type":"education","lineage":["https://openalex.org/I138925566"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Je-Won Kang","raw_affiliation_strings":["Department of Electronic and Electrical Engineering, Ewha W. University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electronic and Electrical Engineering, Ewha W. University, Seoul, Korea","institution_ids":["https://openalex.org/I138925566"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I138925566"],"apc_list":null,"apc_paid":null,"fwci":0.3042,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.66723297,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"3578","last_page":"3582"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998000264167786,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998000264167786,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994999766349792,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9983000159263611,"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/computer-science","display_name":"Computer science","score":0.8251688480377197},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7438750863075256},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7244630455970764},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6441695690155029},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6064845323562622},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5313124656677246},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.529954731464386},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5048165917396545},{"id":"https://openalex.org/keywords/residual-frame","display_name":"Residual frame","score":0.49255070090293884},{"id":"https://openalex.org/keywords/block-matching-algorithm","display_name":"Block-matching algorithm","score":0.477777361869812},{"id":"https://openalex.org/keywords/video-processing","display_name":"Video processing","score":0.47459813952445984},{"id":"https://openalex.org/keywords/video-compression-picture-types","display_name":"Video compression picture types","score":0.4707271158695221},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.4426555633544922},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4408561885356903},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.425537645816803},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3509436845779419},{"id":"https://openalex.org/keywords/reference-frame","display_name":"Reference frame","score":0.3202737867832184},{"id":"https://openalex.org/keywords/multiview-video-coding","display_name":"Multiview Video Coding","score":0.3086243271827698},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1844739019870758}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8251688480377197},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7438750863075256},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7244630455970764},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6441695690155029},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6064845323562622},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5313124656677246},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.529954731464386},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5048165917396545},{"id":"https://openalex.org/C204641915","wikidata":"https://www.wikidata.org/wiki/Q7315509","display_name":"Residual frame","level":4,"score":0.49255070090293884},{"id":"https://openalex.org/C167510206","wikidata":"https://www.wikidata.org/wiki/Q2835824","display_name":"Block-matching algorithm","level":4,"score":0.477777361869812},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.47459813952445984},{"id":"https://openalex.org/C106030495","wikidata":"https://www.wikidata.org/wiki/Q1797012","display_name":"Video compression picture types","level":4,"score":0.4707271158695221},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.4426555633544922},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4408561885356903},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.425537645816803},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3509436845779419},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.3202737867832184},{"id":"https://openalex.org/C23431618","wikidata":"https://www.wikidata.org/wiki/Q1404672","display_name":"Multiview Video Coding","level":4,"score":0.3086243271827698},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1844739019870758},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451079","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451079","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1485009520","https://openalex.org/W2034328688","https://openalex.org/W2099471712","https://openalex.org/W2116435618","https://openalex.org/W2248556341","https://openalex.org/W2401640538","https://openalex.org/W2476548250","https://openalex.org/W2607738331","https://openalex.org/W2615413256","https://openalex.org/W2749658623","https://openalex.org/W2773608377","https://openalex.org/W2962839378","https://openalex.org/W2964303162","https://openalex.org/W4249279051","https://openalex.org/W4294037149","https://openalex.org/W4294554810","https://openalex.org/W4297772798","https://openalex.org/W4320013936","https://openalex.org/W6677326919","https://openalex.org/W6743740970"],"related_works":["https://openalex.org/W2107302173","https://openalex.org/W3132023272","https://openalex.org/W2187171999","https://openalex.org/W3013182045","https://openalex.org/W2782365651","https://openalex.org/W2118574600","https://openalex.org/W2035981816","https://openalex.org/W2946000660","https://openalex.org/W2164320023","https://openalex.org/W2168879190"],"abstract_inverted_index":{"In":[0,110],"this":[1,46],"paper,":[2],"we":[3],"propose":[4],"a":[5,69,93,111],"novel":[6],"long-term":[7,145],"video":[8,29,32,43,66,71,129,146],"generation":[9,147],"algorithm,":[10],"motivated":[11],"by":[12,118],"the":[13,41,48,64,77,81,96,107,113,120,127,135],"recent":[14],"developments":[15],"of":[16,27,76,122,144],"unsupervised":[17],"deep":[18],"learning":[19,82],"techniques.":[20,150],"The":[21,74],"proposed":[22,49,136],"technique":[23,50,137],"learns":[24],"two":[25,52,123],"ingredients":[26],"internal":[28],"representation,":[30],"i.e.,":[31],"textures":[33],"and":[34,68,141],"motions":[35],"to":[36,59],"reproduce":[37],"realistic":[38],"pixels":[39],"in":[40,92,106],"future":[42,108,114],"frames.":[44],"To":[45],"aim,":[47],"uses":[51],"encoders":[53],"comprising":[54],"convolutional":[55],"neural":[56],"networks":[57],"(CNN)":[58],"extract":[60],"spatiotemporal":[61,90],"features":[62],"from":[63],"original":[65,128],"frame":[67,79,115],"residual":[70,78,97],"frame,":[72],"respectively.":[73],"use":[75],"facilitates":[80],"with":[83],"fewer":[84],"parameters":[85],"as":[86],"there":[87],"are":[88,99],"high":[89],"correlations":[91],"video.":[94],"Moreover,":[95],"frames":[98],"efficiently":[100],"used":[101],"for":[102],"evolving":[103],"pixel":[104],"differences":[105],"frame.":[109],"decoder,":[112],"is":[116],"generated":[117],"transforming":[119],"combination":[121],"feature":[124],"vectors":[125],"into":[126],"size.":[130],"Experimental":[131],"results":[132,143],"demonstrate":[133],"that":[134],"provides":[138],"more":[139],"robust":[140],"accurate":[142],"than":[148],"conventional":[149]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}