{"id":"https://openalex.org/W2909704003","doi":"https://doi.org/10.1109/ipta.2018.8608127","title":"Unsupervised Facial Image De-occlusion with Optimized Deep Generative Models","display_name":"Unsupervised Facial Image De-occlusion with Optimized Deep Generative Models","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2909704003","doi":"https://doi.org/10.1109/ipta.2018.8608127","mag":"2909704003"},"language":"en","primary_location":{"id":"doi:10.1109/ipta.2018.8608127","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2018.8608127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"},"type":"article","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/A5101523870","display_name":"Lei Xu","orcid":"https://orcid.org/0000-0003-0115-2770"},"institutions":[{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]},{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":true,"raw_author_name":"Lei Xu","raw_affiliation_strings":["Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland"],"affiliations":[{"raw_affiliation_string":"Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100671939","display_name":"Honglei Zhang","orcid":"https://orcid.org/0000-0002-8229-852X"},"institutions":[{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]},{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Honglei Zhang","raw_affiliation_strings":["Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland"],"affiliations":[{"raw_affiliation_string":"Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055803270","display_name":"Jenni Raitoharju","orcid":"https://orcid.org/0000-0003-4631-9298"},"institutions":[{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]},{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jenni Raitoharju","raw_affiliation_strings":["Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland"],"affiliations":[{"raw_affiliation_string":"Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007583477","display_name":"Moncef Gabbouj","orcid":"https://orcid.org/0000-0002-9788-2323"},"institutions":[{"id":"https://openalex.org/I4210133110","display_name":"Tampere University","ror":null,"country_code":"FI","type":null,"lineage":["https://openalex.org/I4210133110"]},{"id":"https://openalex.org/I166825849","display_name":"Tampere University","ror":"https://ror.org/033003e23","country_code":"FI","type":"education","lineage":["https://openalex.org/I166825849"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Moncef Gabbouj","raw_affiliation_strings":["Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland"],"affiliations":[{"raw_affiliation_string":"Laboratory of Signal Processing, Tampere University of Technology, Tampere, Finland","institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101523870"],"corresponding_institution_ids":["https://openalex.org/I166825849","https://openalex.org/I4210133110"],"apc_list":null,"apc_paid":null,"fwci":0.5223,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.72186507,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"36","issue":null,"first_page":"1","last_page":"6"},"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":0.9991999864578247,"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":0.9991999864578247,"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":0.9990000128746033,"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/T11448","display_name":"Face recognition and analysis","score":0.9937000274658203,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8287553787231445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7583327293395996},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.7260698676109314},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5666701197624207},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5138800144195557},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.49309036135673523},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4917590916156769},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.4910752773284912},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.49090224504470825},{"id":"https://openalex.org/keywords/occlusion","display_name":"Occlusion","score":0.48598822951316833},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4760708212852478},{"id":"https://openalex.org/keywords/generative-adversarial-network","display_name":"Generative adversarial network","score":0.45803216099739075},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.4548538029193878},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42029309272766113},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.41570496559143066},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.36803144216537476},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14852765202522278}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8287553787231445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7583327293395996},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.7260698676109314},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5666701197624207},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5138800144195557},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.49309036135673523},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4917590916156769},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.4910752773284912},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.49090224504470825},{"id":"https://openalex.org/C2776268601","wikidata":"https://www.wikidata.org/wiki/Q968808","display_name":"Occlusion","level":2,"score":0.48598822951316833},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4760708212852478},{"id":"https://openalex.org/C2988773926","wikidata":"https://www.wikidata.org/wiki/Q25104379","display_name":"Generative adversarial network","level":3,"score":0.45803216099739075},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.4548538029193878},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42029309272766113},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.41570496559143066},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.36803144216537476},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14852765202522278},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C164705383","wikidata":"https://www.wikidata.org/wiki/Q10379","display_name":"Cardiology","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipta.2018.8608127","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2018.8608127","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W114517082","https://openalex.org/W184699070","https://openalex.org/W1513463179","https://openalex.org/W1522301498","https://openalex.org/W1710476689","https://openalex.org/W1907580221","https://openalex.org/W2073575766","https://openalex.org/W2085400714","https://openalex.org/W2135453071","https://openalex.org/W2147901574","https://openalex.org/W2151190260","https://openalex.org/W2173520492","https://openalex.org/W2209882149","https://openalex.org/W2275363859","https://openalex.org/W2295936755","https://openalex.org/W2394486593","https://openalex.org/W2437557374","https://openalex.org/W2475287302","https://openalex.org/W2565575913","https://openalex.org/W2611104282","https://openalex.org/W2738588019","https://openalex.org/W2770743355","https://openalex.org/W2791184993","https://openalex.org/W2963420272","https://openalex.org/W2963684088","https://openalex.org/W2963917315","https://openalex.org/W2964121744","https://openalex.org/W2964193438","https://openalex.org/W2994340921","https://openalex.org/W2997095758","https://openalex.org/W4295749397","https://openalex.org/W4298289240","https://openalex.org/W4301054805","https://openalex.org/W6607362247","https://openalex.org/W6631190155","https://openalex.org/W6635552349","https://openalex.org/W6637568146","https://openalex.org/W6683590716","https://openalex.org/W6685352114","https://openalex.org/W6718455164","https://openalex.org/W6746684113","https://openalex.org/W6748645028"],"related_works":["https://openalex.org/W3217069185","https://openalex.org/W3049340819","https://openalex.org/W4308928038","https://openalex.org/W4200430540","https://openalex.org/W3141413246","https://openalex.org/W2997921738","https://openalex.org/W2808862658","https://openalex.org/W2888032422","https://openalex.org/W2806873178","https://openalex.org/W2770818364"],"abstract_inverted_index":{"In":[0,23,118],"recent":[1],"years,":[2],"Generative":[3,48],"Adversarial":[4,49],"Networks":[5,50],"(GANs)":[6],"or":[7,116],"various":[8,160],"types":[9],"of":[10,65,94,104,153,178],"Auto-Encoders":[11],"(AEs)":[12],"have":[13],"gained":[14],"attention":[15],"on":[16,156],"facial":[17,36,86,128,157],"image":[18,87,129],"de-occlusion":[19],"and/or":[20],"in-painting":[21,88],"tasks.":[22],"this":[24,105,137],"paper,":[25],"we":[26],"propose":[27],"a":[28,68,71,92,121,131],"novel":[29,132],"unsupervised":[30,187],"technique":[31],"to":[32,79,141],"remove":[33],"occlusion":[34],"from":[35,125],"images":[37,66,158],"and":[38,70,100,135,165,180],"complete":[39,181],"the":[40,63,97,101,143,151,182],"occluded":[41,127,183],"parts":[42,184],"simultaneously":[43],"with":[44,159],"optimized":[45],"Deep":[46],"Convolutional":[47],"(DCGANs)":[51],"in":[52,185],"an":[53,126,186],"iterative":[54],"way.":[55],"Generally,":[56],"GANs,":[57],"as":[58,74,96,114,163],"generative":[59,111],"models,":[60,112],"can":[61,173],"estimate":[62],"distribution":[64],"using":[67,110,130],"generator":[69],"discriminator.":[72],"DCGANs,":[73],"its":[75,81],"variant,":[76],"are":[77],"proposed":[78],"conquer":[80],"instability":[82],"during":[83],"training.":[84],"Existing":[85],"methods":[89],"manually":[90],"define":[91],"block":[93,106],"pixels":[95],"missing":[98],"part":[99],"potential":[102],"content":[103],"is":[107,123,139],"semantically":[108],"generated":[109],"such":[113,162],"GANs":[115],"AEs.":[117],"our":[119,154,171],"method,":[120],"mask":[122,138],"inferred":[124],"loss":[133],"function,":[134],"then":[136],"utilized":[140],"in-paint":[142],"occlusions":[144,179],"automatically":[145],"by":[146],"pre-trained":[147],"DCGANs.":[148],"We":[149],"evaluate":[150],"performance":[152],"method":[155,172],"occlusions,":[161],"sunglasses":[164],"scarves.":[166],"The":[167],"experiments":[168],"demonstrate":[169],"that":[170],"effectively":[174],"detect":[175],"certain":[176],"kinds":[177],"manner.":[188]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}