{"id":"https://openalex.org/W3128958780","doi":"https://doi.org/10.1109/access.2021.3056144","title":"Adversarial Edge-Aware Image Colorization With Semantic Segmentation","display_name":"Adversarial Edge-Aware Image Colorization With Semantic Segmentation","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3128958780","doi":"https://doi.org/10.1109/access.2021.3056144","mag":"3128958780"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3056144","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3056144","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345804.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345804.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5062492732","display_name":"Guangqian Kong","orcid":"https://orcid.org/0000-0001-6662-2564"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guangqian Kong","raw_affiliation_strings":["School of Computer Science and Technology, Guizhou University, Guiyang, China"],"raw_orcid":"https://orcid.org/0000-0001-6662-2564","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077392257","display_name":"Huan Tian","orcid":"https://orcid.org/0000-0002-6387-8430"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huan Tian","raw_affiliation_strings":["School of Computer Science and Technology, Guizhou University, Guiyang, China"],"raw_orcid":"https://orcid.org/0000-0002-6387-8430","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021561961","display_name":"Xun Duan","orcid":"https://orcid.org/0000-0001-7623-5816"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xun Duan","raw_affiliation_strings":["School of Computer Science and Technology, Guizhou University, Guiyang, China"],"raw_orcid":"https://orcid.org/0000-0001-7623-5816","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026010007","display_name":"Huiyun Long","orcid":"https://orcid.org/0000-0002-6334-413X"},"institutions":[{"id":"https://openalex.org/I178232147","display_name":"Guizhou University","ror":"https://ror.org/02wmsc916","country_code":"CN","type":"education","lineage":["https://openalex.org/I178232147"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyun Long","raw_affiliation_strings":["School of Computer Science and Technology, Guizhou University, Guiyang, China"],"raw_orcid":"https://orcid.org/0000-0002-6334-413X","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Guizhou University, Guiyang, China","institution_ids":["https://openalex.org/I178232147"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I178232147"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.6959,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.85981836,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"28194","last_page":"28203"},"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":0.9993000030517578,"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":0.9993000030517578,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9972000122070312,"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":0.9968000054359436,"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":0.7905975580215454},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.7032225728034973},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.659313440322876},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6284002661705017},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5645143985748291},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5343095064163208},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5309946537017822},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.49136343598365784},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.45168644189834595},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.4203609526157379},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39164745807647705},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3061932921409607}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7905975580215454},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.7032225728034973},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.659313440322876},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6284002661705017},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5645143985748291},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5343095064163208},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5309946537017822},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.49136343598365784},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.45168644189834595},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.4203609526157379},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39164745807647705},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3061932921409607}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3056144","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3056144","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345804.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1ee07debad914b61b7c9858fcff389f6","is_oa":true,"landing_page_url":"https://doaj.org/article/1ee07debad914b61b7c9858fcff389f6","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 9, Pp 28194-28203 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3056144","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3056144","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09345804.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7274162677","display_name":null,"funder_award_id":"61741124","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3128958780.pdf","grobid_xml":"https://content.openalex.org/works/W3128958780.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W2007607024","https://openalex.org/W2055512048","https://openalex.org/W2103155998","https://openalex.org/W2108598243","https://openalex.org/W2117493512","https://openalex.org/W2120963736","https://openalex.org/W2125389028","https://openalex.org/W2136154655","https://openalex.org/W2148520845","https://openalex.org/W2168289460","https://openalex.org/W2194775991","https://openalex.org/W2211456655","https://openalex.org/W2295537950","https://openalex.org/W2308529009","https://openalex.org/W2326925005","https://openalex.org/W2398078772","https://openalex.org/W2461158874","https://openalex.org/W2549139847","https://openalex.org/W2590274298","https://openalex.org/W2612063021","https://openalex.org/W2624871570","https://openalex.org/W2737258237","https://openalex.org/W2792021479","https://openalex.org/W2953276469","https://openalex.org/W2963073614","https://openalex.org/W2963150697","https://openalex.org/W2963170546","https://openalex.org/W2963227409","https://openalex.org/W2963420686","https://openalex.org/W2963904861","https://openalex.org/W3010626953","https://openalex.org/W3039675180","https://openalex.org/W3102726805","https://openalex.org/W6637373629","https://openalex.org/W6639824700","https://openalex.org/W6675306007","https://openalex.org/W6678815747","https://openalex.org/W6739365718","https://openalex.org/W6753238718"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2103507220","https://openalex.org/W3144569342","https://openalex.org/W2945274617","https://openalex.org/W4313052709","https://openalex.org/W4205800335","https://openalex.org/W2055202857","https://openalex.org/W2022929107","https://openalex.org/W80586315","https://openalex.org/W2758994127"],"abstract_inverted_index":{"It":[0],"has":[1],"become":[2],"a":[3,29,43,60,63,73,96],"trend":[4],"in":[5,27,72,131,141],"recent":[6],"years":[7],"to":[8,68,128],"use":[9,95],"deep":[10,64],"neural":[11],"networks":[12],"for":[13,117],"colorization.":[14,143],"However,":[15],"previous":[16],"methods":[17,130],"often":[18],"encounter":[19],"problems":[20],"with":[21,50,54,62,101,110],"edge":[22],"color":[23,31,86,98],"leakage":[24],"and":[25,80,88,114,137],"difficulties":[26],"obtaining":[28],"plausible":[30],"output":[32,52],"from":[33],"the":[34],"Euclidean":[35],"distance.":[36],"To":[37],"solve":[38],"these":[39],"problems,":[40],"we":[41,93],"propose":[42],"new":[44],"adversarial":[45,115],"edge-aware":[46],"image":[47,76,142],"colorization":[48,82],"method":[49,125],"multitask":[51],"combined":[53,109],"semantic":[55,65,70,89,111],"segmentation.":[56],"The":[57,119],"system":[58],"uses":[59],"generator":[61],"fusion":[66],"structure":[67],"infer":[69],"clues":[71],"given":[74],"grayscale":[75],"under":[77],"chroma":[78],"conditions":[79],"learns":[81],"by":[83],"simultaneously":[84],"predicting":[85],"information":[87],"information.":[90],"In":[91],"addition,":[92],"also":[94],"specific":[97],"difference":[99],"loss":[100,113,116],"characteristics":[102],"of":[103,133],"human":[104],"visual":[105],"observation":[106],"that":[107,123],"is":[108,126],"segmentation":[112],"training.":[118],"experimental":[120],"results":[121,140],"show":[122],"our":[124],"superior":[127],"existing":[129],"terms":[132],"different":[134],"quality":[135],"metrics":[136],"achieves":[138],"good":[139]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}