{"id":"https://openalex.org/W4308235900","doi":"https://doi.org/10.1109/icip46576.2022.9897765","title":"Self-Supervised Cooperative Colorization of Achromatic Faces","display_name":"Self-Supervised Cooperative Colorization of Achromatic Faces","publication_year":2022,"publication_date":"2022-10-16","ids":{"openalex":"https://openalex.org/W4308235900","doi":"https://doi.org/10.1109/icip46576.2022.9897765"},"language":"en","primary_location":{"id":"doi:10.1109/icip46576.2022.9897765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897765","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Image Processing (ICIP)","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/A5112959111","display_name":"Hitika Tiwari","orcid":null},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]},{"id":"https://openalex.org/I148366613","display_name":"National Yang Ming Chiao Tung University","ror":"https://ror.org/00se2k293","country_code":"TW","type":"education","lineage":["https://openalex.org/I148366613"]}],"countries":["IN","TW"],"is_corresponding":true,"raw_author_name":"Hitika Tiwari","raw_affiliation_strings":["Indian Institute of Technology,Kanpur,India","National Yang Ming Chiao Tung University, Taiwan","Indian Institute of Technology, Kanpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Kanpur,India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"National Yang Ming Chiao Tung University, Taiwan","institution_ids":["https://openalex.org/I148366613"]},{"raw_affiliation_string":"Indian Institute of Technology, Kanpur, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101741116","display_name":"Venkatesh K. Subramanian","orcid":null},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Venkatesh K. Subramanian","raw_affiliation_strings":["Indian Institute of Technology,Kanpur,India","Indian Institute of Technology, Kanpur, India"],"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology,Kanpur,India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"Indian Institute of Technology, Kanpur, India","institution_ids":["https://openalex.org/I94234084"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5112959111"],"corresponding_institution_ids":["https://openalex.org/I148366613","https://openalex.org/I94234084"],"apc_list":null,"apc_paid":null,"fwci":0.0599,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.28739484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"236","last_page":"240"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9995999932289124,"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/T11448","display_name":"Face recognition and analysis","score":0.9995999932289124,"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":0.9952999949455261,"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":0.9836000204086304,"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/achromatic-lens","display_name":"Achromatic lens","score":0.9774240255355835},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8165453672409058},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7196763753890991},{"id":"https://openalex.org/keywords/chromatic-scale","display_name":"Chromatic scale","score":0.704689085483551},{"id":"https://openalex.org/keywords/colored","display_name":"Colored","score":0.6826602816581726},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6425234079360962},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5806411504745483},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5754538178443909},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4321174621582031},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4260559678077698},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.140518456697464},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11111509799957275},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08421069383621216}],"concepts":[{"id":"https://openalex.org/C121535716","wikidata":"https://www.wikidata.org/wiki/Q340600","display_name":"Achromatic lens","level":2,"score":0.9774240255355835},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8165453672409058},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7196763753890991},{"id":"https://openalex.org/C196956537","wikidata":"https://www.wikidata.org/wiki/Q202021","display_name":"Chromatic scale","level":2,"score":0.704689085483551},{"id":"https://openalex.org/C2778307483","wikidata":"https://www.wikidata.org/wiki/Q5149038","display_name":"Colored","level":2,"score":0.6826602816581726},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6425234079360962},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5806411504745483},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5754538178443909},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4321174621582031},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4260559678077698},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.140518456697464},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11111509799957275},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08421069383621216},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip46576.2022.9897765","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip46576.2022.9897765","pdf_url":null,"source":{"id":"https://openalex.org/S4363607719","display_name":"2022 IEEE International Conference on Image Processing (ICIP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 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":19,"referenced_works":["https://openalex.org/W1834627138","https://openalex.org/W2096733369","https://openalex.org/W2237250383","https://openalex.org/W2519131448","https://openalex.org/W2798291180","https://openalex.org/W2912459656","https://openalex.org/W2952080583","https://openalex.org/W2962780596","https://openalex.org/W2962793481","https://openalex.org/W2963805028","https://openalex.org/W2964449965","https://openalex.org/W3005062323","https://openalex.org/W3034512702","https://openalex.org/W3101531717","https://openalex.org/W3123542644","https://openalex.org/W3155080005","https://openalex.org/W3172500391","https://openalex.org/W3206505499","https://openalex.org/W4213274538"],"related_works":["https://openalex.org/W2181667894","https://openalex.org/W1971049897","https://openalex.org/W2087227609","https://openalex.org/W1964564375","https://openalex.org/W1966026245","https://openalex.org/W2132521003","https://openalex.org/W2603119503","https://openalex.org/W2099314438","https://openalex.org/W2117158375","https://openalex.org/W4239527754"],"abstract_inverted_index":{"Despite":[0],"the":[1,20,24,31,44,57,90,109,116,146,149],"recent":[2],"progress":[3],"in":[4],"deep":[5],"learning-based":[6],"face":[7,33,41,100],"image":[8],"colorization":[9,34],"techniques,":[10],"there":[11],"is":[12,23,55],"still":[13],"much":[14],"room":[15],"for":[16,125],"improvement.":[17],"One":[18],"of":[19,46,59,76,94,143,148],"significant":[21],"challenges":[22],"bias":[25],"toward":[26],"specific":[27,105],"skin":[28],"color.":[29],"Moreover,":[30],"conventional":[32],"approaches":[35],"aim":[36],"to":[37,87,135,140],"produce":[38],"colored":[39,47],"2D":[40],"images,":[42],"whereas":[43],"generation":[45],"3D":[48,95,126],"faces":[49,96],"from":[50,131],"monocular":[51,98],"achromatic":[52,85,99],"(gray-scale)":[53],"images":[54,101],"beyond":[56],"scope":[58],"these":[60,69],"methods":[61],"despite":[62],"having":[63],"immense":[64],"potential":[65],"applications.":[66],"To":[67],"address":[68],"issues,":[70],"we":[71],"propose":[72],"Self-Supervised":[73],"COoperative":[74],"COlorizaTion":[75],"Achromatic":[77],"Faces":[78],"(COCOTA)":[79],"framework":[80],"that":[81],"contains":[82],"chromatic":[83],"and":[84,92],"pipelines":[86],"jointly":[88],"estimate":[89],"color":[91,106],"shape":[93],"using":[97],"without":[102],"inducing":[103],"any":[104],"bias.":[107],"On":[108],"challenging":[110],"CelebA":[111],"test":[112],"dataset,":[113],"COCOTA":[114],"out-performs":[115],"current":[117],"state-of-the-art":[118],"method":[119],"by":[120],"a":[121,129],"large":[122],"margin":[123],"(e.g.,":[124],"color-based":[127],"error,":[128],"reduction":[130],"5.12":[132],"\u00b1":[133,137],"0.13":[134],"3.09":[136],"0.08":[138],"leading":[139],"an":[141],"improvement":[142],"39.6%),":[144],"demonstrating":[145],"effectiveness":[147],"proposed":[150],"method.":[151]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}