{"id":"https://openalex.org/W2970592216","doi":"https://doi.org/10.1109/icip.2019.8803052","title":"A Coarse-to-Fine Framework for Learned Color Enhancement with Non-Local Attention","display_name":"A Coarse-to-Fine Framework for Learned Color Enhancement with Non-Local Attention","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970592216","doi":"https://doi.org/10.1109/icip.2019.8803052","mag":"2970592216"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5049650831","display_name":"Chaowei Shan","orcid":"https://orcid.org/0000-0001-9597-4155"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Chaowei Shan","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101734732","display_name":"Zhizheng Zhang","orcid":"https://orcid.org/0000-0002-5360-7565"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhizheng Zhang","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079572598","display_name":"Zhibo Chen","orcid":"https://orcid.org/0000-0002-8525-5066"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhibo Chen","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5049650831"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.1012,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.43515694,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"949","last_page":"953"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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/T11019","display_name":"Image Enhancement Techniques","score":1.0,"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":0.9993000030517578,"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/T10531","display_name":"Advanced Vision and Imaging","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":0.781996488571167},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.669354259967804},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.657537579536438},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.592261552810669},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.5690094828605652},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5398876070976257},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5179316401481628},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5078335404396057},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4947468638420105},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4946076571941376},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4359988570213318},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4113258421421051},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3530508279800415},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.27523568272590637},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09863749146461487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.781996488571167},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.669354259967804},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.657537579536438},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.592261552810669},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.5690094828605652},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5398876070976257},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5179316401481628},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5078335404396057},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4947468638420105},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4946076571941376},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4359988570213318},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4113258421421051},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3530508279800415},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27523568272590637},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09863749146461487},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1665214252","https://openalex.org/W1836465849","https://openalex.org/W1920280450","https://openalex.org/W2025328853","https://openalex.org/W2099471712","https://openalex.org/W2113636985","https://openalex.org/W2125389028","https://openalex.org/W2147800946","https://openalex.org/W2149049515","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2242218935","https://openalex.org/W2331128040","https://openalex.org/W2607202125","https://openalex.org/W2798844427","https://openalex.org/W2889625055","https://openalex.org/W2962793481","https://openalex.org/W2963073614","https://openalex.org/W2963091558","https://openalex.org/W2963156339","https://openalex.org/W2963452532","https://openalex.org/W2963967766","https://openalex.org/W4230472795","https://openalex.org/W4320013936","https://openalex.org/W6637242042","https://openalex.org/W6638667902","https://openalex.org/W6656529242","https://openalex.org/W6678815747","https://openalex.org/W6684191040","https://openalex.org/W6702130928","https://openalex.org/W6754215068"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W4230315250","https://openalex.org/W2086519370","https://openalex.org/W2087343574"],"abstract_inverted_index":{"Automatic":[0],"color":[1,52],"enhancement":[2,53,64,68],"are":[3,29],"aimed":[4],"to":[5,11,31,62,96,122,149],"automaticly":[6],"and":[7,14,26,69,145],"adaptively":[8],"adjust":[9],"photos":[10],"expected":[12],"styles":[13],"tones.":[15],"For":[16],"current":[17],"learned":[18],"methods":[19],"in":[20,34,54],"this":[21,41,55],"field,":[22],"global":[23,87,98,128],"harmonious":[24],"perception":[25],"local":[27,113,133],"details":[28],"hard":[30],"be":[32],"well-considered":[33],"a":[35,45,86,106,118],"single":[36],"model":[37,84],"simultaneously.":[38],"To":[39],"address":[40],"problem,":[42],"we":[43,60,104,116],"propose":[44,61],"coarse-to-fine":[46],"framework":[47,139],"with":[48],"non-local":[49,119],"attention":[50,120],"for":[51,90,112,130],"paper.":[56],"Within":[57],"our":[58,83,137],"framework,":[59],"divide":[63],"process":[65],"into":[66],"channel-wise":[67,81],"pixel-wise":[70,102],"refinement":[71],"performed":[72],"by":[73],"two":[74],"cascaded":[75],"Convolutional":[76],"Neural":[77],"Networks":[78],"(CNNs).":[79],"In":[80,101],"enhancement,":[82],"predicts":[85],"linear":[88],"mapping":[89,108],"RGB":[91],"channels":[92],"of":[93],"input":[94],"images":[95],"perform":[97],"style":[99],"adjustment.":[100,114],"refinement,":[103],"learn":[105],"refining":[107],"using":[109,143],"residual":[110],"learning":[111],"Further,":[115],"adopt":[117],"block":[121],"capture":[123],"the":[124,141],"long-range":[125],"dependencies":[126],"from":[127],"information":[129],"subsequent":[131],"fine-grained":[132],"refinement.":[134],"We":[135],"evaluate":[136],"proposed":[138],"on":[140],"commonly":[142],"benchmark":[144],"conduct":[146],"sufficient":[147],"experiments":[148],"demonstrate":[150],"each":[151],"technical":[152],"component":[153],"within":[154],"it.":[155]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
