{"id":"https://openalex.org/W2991005701","doi":"https://doi.org/10.1109/tip.2019.2955640","title":"Self-Enhanced Convolutional Network for Facial Video Hallucination","display_name":"Self-Enhanced Convolutional Network for Facial Video Hallucination","publication_year":2019,"publication_date":"2019-12-03","ids":{"openalex":"https://openalex.org/W2991005701","doi":"https://doi.org/10.1109/tip.2019.2955640","mag":"2991005701"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2019.2955640","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2955640","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1911.11136","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Chaowei Fang","orcid":"https://orcid.org/0000-0001-8805-9792"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["CN","HK"],"is_corresponding":true,"raw_author_name":"Chaowei Fang","raw_affiliation_strings":["Department of Computer Science, The University of Hong Kong, Hong Kong","School of Artificial Intelligence, Xidian University, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0000-0001-8805-9792","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]},{"raw_affiliation_string":"School of Artificial Intelligence, Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Guanbin Li","orcid":"https://orcid.org/0000-0002-4805-0926"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guanbin Li","raw_affiliation_strings":["School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4805-0926","affiliations":[{"raw_affiliation_string":"School of Data and Computer Science, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Xiaoguang Han","orcid":"https://orcid.org/0000-0003-0162-3296"},"institutions":[{"id":"https://openalex.org/I4210099586","display_name":"Shenzhen Research Institute of Big Data","ror":"https://ror.org/00z1gwf89","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210099586"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoguang Han","raw_affiliation_strings":["Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-0162-3296","affiliations":[{"raw_affiliation_string":"Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I4210116924","https://openalex.org/I4210099586"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yizhou Yu","orcid":"https://orcid.org/0000-0002-0470-5548"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Yizhou Yu","raw_affiliation_strings":["Department of Computer Science, The University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-0470-5548","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I149594827","https://openalex.org/I889458895"],"apc_list":null,"apc_paid":null,"fwci":0.4083,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.66711824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"29","issue":null,"first_page":"3078","last_page":"3090"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.9833999872207642,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9833999872207642,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.008299999870359898,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.0012000000569969416,"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/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6401000022888184},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5382000207901001},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47269999980926514},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46720001101493835},{"id":"https://openalex.org/keywords/coherence","display_name":"Coherence (philosophical gambling strategy)","score":0.453000009059906},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.39500001072883606},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.3937999904155731},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.38769999146461487},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.37130001187324524}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8460999727249146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7372000217437744},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6401000022888184},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5382000207901001},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5080999732017517},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47269999980926514},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46720001101493835},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.453000009059906},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.39500001072883606},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3937999904155731},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.38769999146461487},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3684000074863434},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.3637000024318695},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3634999990463257},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.358599990606308},{"id":"https://openalex.org/C54654163","wikidata":"https://www.wikidata.org/wiki/Q5428359","display_name":"Face hallucination","level":5,"score":0.3481000065803528},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.3321000039577484},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2897000014781952},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.2896000146865845},{"id":"https://openalex.org/C65483669","wikidata":"https://www.wikidata.org/wiki/Q3536669","display_name":"Video processing","level":2,"score":0.28700000047683716},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2856000065803528},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.27730000019073486},{"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/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.26420000195503235},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.25949999690055847},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.25769999623298645}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2019.2955640","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2019.2955640","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1911.11136","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.11136","pdf_url":"https://arxiv.org/pdf/1911.11136","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1911.11136","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1911.11136","pdf_url":"https://arxiv.org/pdf/1911.11136","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1874218645","display_name":null,"funder_award_id":"61976250","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1945170033","display_name":null,"funder_award_id":"18lgpy63","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3577923441","display_name":null,"funder_award_id":"U1811463","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5589842934","display_name":null,"funder_award_id":"R-5001-18","funder_id":"https://openalex.org/F4320307285","funder_display_name":"Impact Fund"},{"id":"https://openalex.org/G5883456296","display_name":null,"funder_award_id":"2018B030338001","funder_id":"https://openalex.org/F4320324202","funder_display_name":"Guangdong Science and Technology Department"},{"id":"https://openalex.org/G7805870020","display_name":null,"funder_award_id":"KQTD2015033114415450","funder_id":"https://openalex.org/F4320335803","funder_display_name":"Shenzhen Fundamental Research and Discipline Layout project"},{"id":"https://openalex.org/G982156559","display_name":null,"funder_award_id":"ZDSYS201707251409055","funder_id":"https://openalex.org/F4320335803","funder_display_name":"Shenzhen Fundamental Research and Discipline Layout project"}],"funders":[{"id":"https://openalex.org/F4320307285","display_name":"Impact Fund","ror":"https://ror.org/00jb20j87"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320324202","display_name":"Guangdong Science and Technology Department","ror":"https://ror.org/00tjzgn92"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null},{"id":"https://openalex.org/F4320335803","display_name":"Shenzhen Fundamental Research and Discipline Layout project","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1950594372","https://openalex.org/W2010981316","https://openalex.org/W2131774270","https://openalex.org/W2194775991","https://openalex.org/W2320725294","https://openalex.org/W2557227117","https://openalex.org/W2607041014","https://openalex.org/W2726582817","https://openalex.org/W2738579427","https://openalex.org/W2740535357","https://openalex.org/W2752782242","https://openalex.org/W2776107444","https://openalex.org/W2780624730","https://openalex.org/W2781335552","https://openalex.org/W2798664922","https://openalex.org/W2810518847","https://openalex.org/W2904629716","https://openalex.org/W2943792112","https://openalex.org/W2962927175","https://openalex.org/W2963091558","https://openalex.org/W2963186101","https://openalex.org/W2963446712","https://openalex.org/W2963470893","https://openalex.org/W2963583792","https://openalex.org/W2963676087","https://openalex.org/W2964040059","https://openalex.org/W2964101377","https://openalex.org/W2964286567","https://openalex.org/W6628877408","https://openalex.org/W6631190155","https://openalex.org/W6637242042","https://openalex.org/W6640021355","https://openalex.org/W6686186229","https://openalex.org/W6687752125","https://openalex.org/W6698129831","https://openalex.org/W6726691688","https://openalex.org/W6735913928","https://openalex.org/W6738080645","https://openalex.org/W6740167877","https://openalex.org/W6754405603","https://openalex.org/W6779669310"],"related_works":[],"abstract_inverted_index":{"As":[0],"a":[1,10,61,81,104,125,178],"domain-specific":[2],"super-resolution":[3,134,176],"problem,":[4],"facial":[5,66,145],"image":[6],"hallucination":[7],"has":[8],"enjoyed":[9],"series":[11],"of":[12,18,27,43,53,76,84,97,106,124,127,135,143,156,173],"breakthroughs":[13],"thanks":[14],"to":[15,30,35,40,130],"the":[16,24,89,93,118,132,136,141,154,157,171],"advances":[17],"deep":[19],"convolutional":[20,63],"neural":[21],"networks.":[22],"However,":[23],"direct":[25],"migration":[26],"existing":[28],"methods":[29],"video":[31,67,175],"is":[32,70],"still":[33],"difficult":[34],"achieve":[36],"good":[37],"performance":[38,169],"due":[39],"its":[41],"lack":[42],"alignment":[44],"and":[45,80,121,150],"consistency":[46,112],"modelling":[47,140],"in":[48,57,170,177],"temporal":[49,82,111],"domain.":[50],"Taking":[51],"advantage":[52],"high":[54],"inter-frame":[55],"dependency":[56],"videos,":[58],"we":[59],"propose":[60],"self-enhanced":[62],"network":[64],"for":[65],"hallucination.":[68],"It":[69,114],"implemented":[71],"by":[72,100,139],"making":[73],"full":[74],"usage":[75],"preceding":[77,128],"super-resolved":[78],"frames":[79,129],"window":[83],"adjacent":[85],"low-resolution":[86,108],"frames.":[87,148],"Specifically,":[88],"algorithm":[90,159,165],"first":[91],"obtains":[92],"initial":[94,133],"high-resolution":[95],"inference":[96],"each":[98],"frame":[99,138],"taking":[101],"into":[102],"consideration":[103],"sequence":[105,126],"consecutive":[107],"inputs":[109],"through":[110],"modelling.":[113],"further":[115],"recurrently":[116],"exploits":[117],"reconstructed":[119],"results":[120],"intermediate":[122],"features":[123,146],"improve":[131],"current":[137],"coherence":[142],"structural":[144],"across":[147],"Quantitative":[149],"qualitative":[151],"evaluations":[152],"demonstrate":[153],"superiority":[155],"proposed":[158],"against":[160],"state-of-the-art":[161],"methods.":[162],"Moreover,":[163],"our":[164],"also":[166],"achieves":[167],"excellent":[168],"task":[172],"general":[174],"single-shot":[179],"setting.":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2026-05-30T09:04:40.226872","created_date":"2019-12-05T00:00:00"}